- Is your enterprise technology built in a modular way?
- Can you modify or replace a component without affecting other parts of the technology architecture?
- Is your technology platform built with plug and play elements to allow for rapid change and adaptation to business and customer forces?
- Do you employ Agile processes to make calculated changes incrementally?
Technology architecture and implementation governed by a coherent platform strategy that prioritizes flexibility and component and service independence will deliver business impact.
In this paper, we articulate technology platform and architecture requirements to support modern ways of delivering iterative value, increasing the velocity, productivity, and performance of the organization, and reducing product and service time to market.
Metadata is hotter than ever, according to a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information.
While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to todayโs organization, and provide insights into building successful business strategies for metadata adoption & use.
Building a Data Strategy โ Practical Steps for Aligning with Business GoalsDATAVERSITY
ย
Developing a Data Strategy for your organization can seem like a daunting task โ but itโs worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in todayโs marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
ย
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
DAS Slides: Master Data Management โ Aligning Data, Process, and GovernanceDATAVERSITY
ย
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as Customers, Products, Vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous โ from real-time operational integration to data warehousing & analytic reporting. This webinar provides practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Master Data Management - Aligning Data, Process, and GovernanceDATAVERSITY
ย
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM โrightโ requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the โsweet spotโ between technology, design, process, and people for your MDM initiative.
Measuring data quality is on the data management agenda at many financial firms as they seek to reduce operational costs, meet regulatory requirements and identify new product potential. The webinar will consider how metrics can be implemented to provide meaningful measures of data quality that can be used across the firm, solutions for data quality measurement, and the outcomes of successful metrics projects implemented by data management practitioners.
Join the webinar to find out about:
-Challenges of data quality
-Requirements for data quality metrics
-Best practice implementation
-Technology solutions
-User experiences
Metadata is hotter than ever, according to a number of recent DATAVERSITY surveys. More and more organizations are realizing that in order to drive business value from data, robust metadata is needed to gain the necessary context and lineage around key data assets. At the same time, industry regulations are driving the need for better transparency and understanding of information.
While metadata has been managed for decades, new strategies & approaches have been developed to support the ever-evolving data landscape, and provide more innovative ways to drive business value from metadata. This webinar will provide an overview of metadata strategies & technologies available to todayโs organization, and provide insights into building successful business strategies for metadata adoption & use.
Building a Data Strategy โ Practical Steps for Aligning with Business GoalsDATAVERSITY
ย
Developing a Data Strategy for your organization can seem like a daunting task โ but itโs worth the effort. Getting your Data Strategy right can provide significant value, as data drives many of the key initiatives in todayโs marketplace, from digital transformation to marketing, customer centricity, population health, and more. This webinar will help demystify Data Strategy and its relationship to Data Architecture and will provide concrete, practical ways to get started.
DAS Slides: Data Governance - Combining Data Management with Organizational ...DATAVERSITY
ย
Data Governance is both a technical and an organizational discipline, and getting Data Governance right requires a combination of Data Management fundamentals aligned with organizational change and stakeholder buy-in. Join Nigel Turner and Donna Burbank as they provide an architecture-based approach to aligning business motivation, organizational change, Metadata Management, Data Architecture and more in a concrete, practical way to achieve success in your organization.
DAS Slides: Master Data Management โ Aligning Data, Process, and GovernanceDATAVERSITY
ย
Master Data Management (MDM) provides organizations with an accurate and comprehensive view of their business-critical data such as Customers, Products, Vendors, and more. While mastering these key data areas can be a complex task, the value of doing so can be tremendous โ from real-time operational integration to data warehousing & analytic reporting. This webinar provides practical strategies for gaining value from your MDM initiative, while at the same time assuring a solid architectural and governance foundation that will ensure long-term, enterprise-wide success.
Master Data Management - Aligning Data, Process, and GovernanceDATAVERSITY
ย
Master Data Management (MDM) can provide significant value to the organization in creating consistent key data assets such as Customer, Product, Supplier, Patient, and the list goes on. But getting MDM โrightโ requires a strategic mix of Data Architecture, business process, and Data Governance. Join this webinar to learn how to find the โsweet spotโ between technology, design, process, and people for your MDM initiative.
Measuring data quality is on the data management agenda at many financial firms as they seek to reduce operational costs, meet regulatory requirements and identify new product potential. The webinar will consider how metrics can be implemented to provide meaningful measures of data quality that can be used across the firm, solutions for data quality measurement, and the outcomes of successful metrics projects implemented by data management practitioners.
Join the webinar to find out about:
-Challenges of data quality
-Requirements for data quality metrics
-Best practice implementation
-Technology solutions
-User experiences
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to cope with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic expectations, and help demonstrate the value of this process to both internal and external decision makers.
ADV Slides: How to Improve Your Analytic Data Architecture MaturityDATAVERSITY
ย
Many organizations are immature when it comes to data use. The answer lies in delivering a greater level of insight from data, straight to the point of need. Enter: machine learning.
In this webinar, William will look at categories of organizational response to the challenge across strategy, architecture, modeling, processes, and ethics. Machine learning maturity levels tend to move in harmony across these categories. As a general principle of maturity models, you canโt skip levels in any category, nor can you advance in one category well beyond the others.
Vis-ร -vis ML, attaining and retaining momentum up the model is paramount for success. You will ascend the model through concerted efforts delivering business wins utilizing progressive elements of the model, and thereby increasing your machine learning maturity. The model will evolve. No plateaus are comfortable for long.
With ML maturity markers, sequencing, and tactics, this webinar provides a plan for how to build analytic Data Architecture maturity in your organization.
ADV Slides: Organizational Change Management in Becoming an Analytic Organiza...DATAVERSITY
ย
The disparity between expecting change and managing it โ the โchange gapโ โ is growing at an unprecedented pace. This has put many information management shops into traction as they initiate large, complex projects needed to stay competitive.
Information management professionals and business leaders must concern themselves with the organizationโs acceptance of these efforts. To be successful in achieving the larger enterprise goals, these initiatives must transform the organization. However, it takes more than wishful thinking to bridge the gap.
The complexities of engaging behavioral and enterprise transformation are too often underestimated at great peril, because the โsoft stuffโ is truly hard. In this webinar, William McKnight will outline:
โข The change readiness activities that focus on identifying and addressing people risks
โข The tasks that will mobilize and align leaders to create outstanding business value
โข The strategies to manage stakeholders, ensure change readiness, and address the organizational implications
โข The methodologies to train the workforce as required to fully embrace and utilize the system
The Data Quality Assessment Manager is a Data Quality product specifically designed to manage data quality assessments, manage data quality scores, review and correct quality issues and manage the workflow across all stakeholders involved in a data quality assessment. DQAM is the industryโs first platform designed to put data quality in the hands of data stewards and business owners who know and understand the data the best.
This presentation contains strategies that BI groups within IT can use to maximize their productivity and value to the business. It contains an overview of why and how โagile BIโ is used at direct-marketing leader Valpak, and several other strategies that can be employed to help deliver timely, effective BI solutions.
Data Architecture Strategies: Building an Enterprise Data Strategy โ Where to...DATAVERSITY
ย
The majority of successful organizations in todayโs economy are data-driven, and innovative companies are looking at new ways to leverage data and information for strategic advantage. While the opportunities are vast, and the value has clearly been shown across a number of industries in using data to strategic advantage, the choices in technology can be overwhelming. From Big Data to Artificial Intelligence to Data Lakes and Warehouses, the industry is continually evolving to provide new and exciting technological solutions.
This webinar will help make sense of the various data architectures & technologies available, and how to leverage them for business value and success. A practical framework will be provided to generate โquick winsโ for your organization, while at the same time building towards a longer-term sustainable architecture. Case studies will also be provided to show how successful organizations have successfully built a data strategies to support their business goals.
Measuring Data Quality Return on InvestmentDATAVERSITY
ย
Data Quality is an elusive subject that can defy measurement and yet be critical enough to derail any project, strategic initiative, or even a company. The data layer of an organization is a critical component because it is so easy to ignore the quality of that data or to make overly optimistic assumptions about its efficacy. Having Data Quality as a focus is a business philosophy that aligns strategy, business culture, company information, and technology in order to manage data to the benefit of the enterprise. It is a competitive strategy.
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data ...DATAVERSITY
ย
Data can provide tremendous value to an organization in todayโs information-driven economy. New customer insights, better efficiency, and new product innovation are just some of the ways organizations are obtaining value through data. But in order to achieve this value, a strong data architecture is required to ensure that the data infrastructure runs smoothly, while at the same time aligning with business needs and corporate culture. A Data Strategy can assist in building a data architecture foundation through:
Identifying business requirements, rules & definitions via a business-centric data model
Creating a data inventory & integrating disparate data sources
Building a technical data architecture through data models & related artifacts
Coordinating the people, processes and culture necessary for success
Identifying tools & technology needed for creating & maintaining high quality data
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DATAVERSITY
ย
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in todayโs marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
ADV Slides: Databases vs Hadoop vs Cloud StorageDATAVERSITY
ย
Relational databases are old technology, right? Thirty years is a long time for a technology foundation to be as active as relational databases, but, like NFL coaches, we must โtolerate them until we can replace them.โ Are their replacements here? In this webinar, we say no.
Databases have not sat around while Hadoop emerged. The Hadoop era generated a ton of interest and confusion, but is it still relevant as organizations are deploying cloud storage options like a kid in a candy store? Weโll discuss Hadoopโs continued potential relevance and the cloud storage option that seems vital. Use what when? This is a critical decision that can dictate two to five times additional work effort if itโs a bad fit.
Drop the herd mentality. In reality, there is no โone size fits allโ right now. We need to make our platform decisions against this backdrop.
This webinar will distinguish these analytic deployment options and help you platform 2019 for success.
While many Digital Transformation initiatives are focused on improving the customer experience, often too little attention is paid to the customer-facing operational decisions that impact customers every day. To get the most from your Digital Transformation efforts, your customersโ experience and the decisions that impact it cannot be ignored.
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers.
Takeaways:
Organizational thinking must change: Value-added data management practices must be considered and included as a vital part of your business strategy.
Walk before you run with data focused initiatives: Understand and implement necessary data management prerequisites as a foundation, then build upon that foundation.
There are no silver bullets: Tools alone are not the answer. Specifying business requirements, business practices and data governance are almost always more important.
Data Governance โ Aligning Technical and Business ApproachesDATAVERSITY
ย
Data Governance can have a varied definition, depending on the audience. To many, data governance consists of committee meetings and stewardship roles. To others, it focuses on technical data management and controls. Holistic data governance combines both of these aspects, and a robust data architecture and associated diagrams can be the โglueโ that binds business and IT governance together. Join this webinar for practical tips and hands-on exercises for aligning data architecture & data governance for business and IT success.
Social media and relationship development for salesEconsultancy
ย
Econsultancy Director Peter Abraham's presentation on the topic of social media and relationship development for sales. (originally presented at Chicago Booth University School of Business)
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
ย
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Modernizing the Enterprise Monolith: EQengineered Consulting Green PaperRachel Mezzatesta
ย
Are you an enterprise that recognizes the business liability inherent in the monolithic or otherwise dated enterprise software applications you have built? Does your technology represent an impediment to the needed agility and flexibility required to meet the needs of todayโs business environment?
Historically, enterprise software development focused on an approach that incorporated all functionality into a single process, and replicated it across servers as additional capacity was required. Today, these large applications have become bloated and unmanageable as new features and functionality are added. And, as small changes are made to existing functionality, the requirements to update and redeploy the server-side application becomes an intractable juggernaut.
Forward-thinking organizations like Amazon and Netflix led the way toward agile processes, deconstructed software stacks, and efficient APIs. Both large and small organizations serious about embracing modern practices have followed by decoupling the front and back end of their enterprise applications, employing microservices and cloud technologies, and adopting agile methodologies. These very steps can serve to highlight additional technical deficits in old solutions and codebases, which in turn become stumbling blocks to modern development practices.
As these technology trends continue to evolve, how can your company keep pace and remain viable?
In this green paper, we discuss how CIOs, CTOs, and VPs of Engineering can lead the needed modernization with their counterparts in marketing and the business to ensure that their organizations remain competitive in todayโs customer-driven and technology-led economy.
Key questions addressed include:
โข Why is technical modernization vital for the business?
โข What types of modernization projects are there?
โข How does modernization fit into your organization?
Modernizing the Enterprise Monolith: EQengineered Consulting Green PaperMark Hewitt
ย
Are you an enterprise that recognizes the business liability inherent in the monolithic or otherwise dated enterprise software applications you have built? Does your technology represent an impediment to the needed agility and flexibility required to meet the needs of todayโs business environment?
Historically, enterprise software development focused on an approach that incorporated all functionality into a single process, and replicated it across servers as additional capacity was required. Today, these large applications have become bloated and unmanageable as new features and functionality are added. And, as small changes are made to existing functionality, the requirements to update and redeploy the server-side application becomes an intractable juggernaut.
Forward-thinking organizations like Amazon and Netflix led the way toward agile processes, deconstructed software stacks, and efficient APIs. Both large and small organizations serious about embracing modern practices have followed by decoupling the front and back end of their enterprise applications, employing microservices and cloud technologies, and adopting agile methodologies. These very steps can serve to highlight additional technical deficits in old solutions and codebases, which in turn become stumbling blocks to modern development practices.
As these technology trends continue to evolve, how can your company keep pace and remain viable?
In this green paper, we discuss how CIOs, CTOs, and VPs of Engineering can lead the needed modernization with their counterparts in marketing and the business to ensure that their organizations remain competitive in todayโs customer-driven and technology-led economy.
Key questions addressed include:
โข Why is technical modernization vital for the business?
โข What types of modernization projects are there?
โข How does modernization fit into your organization?
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to cope with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic expectations, and help demonstrate the value of this process to both internal and external decision makers.
ADV Slides: How to Improve Your Analytic Data Architecture MaturityDATAVERSITY
ย
Many organizations are immature when it comes to data use. The answer lies in delivering a greater level of insight from data, straight to the point of need. Enter: machine learning.
In this webinar, William will look at categories of organizational response to the challenge across strategy, architecture, modeling, processes, and ethics. Machine learning maturity levels tend to move in harmony across these categories. As a general principle of maturity models, you canโt skip levels in any category, nor can you advance in one category well beyond the others.
Vis-ร -vis ML, attaining and retaining momentum up the model is paramount for success. You will ascend the model through concerted efforts delivering business wins utilizing progressive elements of the model, and thereby increasing your machine learning maturity. The model will evolve. No plateaus are comfortable for long.
With ML maturity markers, sequencing, and tactics, this webinar provides a plan for how to build analytic Data Architecture maturity in your organization.
ADV Slides: Organizational Change Management in Becoming an Analytic Organiza...DATAVERSITY
ย
The disparity between expecting change and managing it โ the โchange gapโ โ is growing at an unprecedented pace. This has put many information management shops into traction as they initiate large, complex projects needed to stay competitive.
Information management professionals and business leaders must concern themselves with the organizationโs acceptance of these efforts. To be successful in achieving the larger enterprise goals, these initiatives must transform the organization. However, it takes more than wishful thinking to bridge the gap.
The complexities of engaging behavioral and enterprise transformation are too often underestimated at great peril, because the โsoft stuffโ is truly hard. In this webinar, William McKnight will outline:
โข The change readiness activities that focus on identifying and addressing people risks
โข The tasks that will mobilize and align leaders to create outstanding business value
โข The strategies to manage stakeholders, ensure change readiness, and address the organizational implications
โข The methodologies to train the workforce as required to fully embrace and utilize the system
The Data Quality Assessment Manager is a Data Quality product specifically designed to manage data quality assessments, manage data quality scores, review and correct quality issues and manage the workflow across all stakeholders involved in a data quality assessment. DQAM is the industryโs first platform designed to put data quality in the hands of data stewards and business owners who know and understand the data the best.
This presentation contains strategies that BI groups within IT can use to maximize their productivity and value to the business. It contains an overview of why and how โagile BIโ is used at direct-marketing leader Valpak, and several other strategies that can be employed to help deliver timely, effective BI solutions.
Data Architecture Strategies: Building an Enterprise Data Strategy โ Where to...DATAVERSITY
ย
The majority of successful organizations in todayโs economy are data-driven, and innovative companies are looking at new ways to leverage data and information for strategic advantage. While the opportunities are vast, and the value has clearly been shown across a number of industries in using data to strategic advantage, the choices in technology can be overwhelming. From Big Data to Artificial Intelligence to Data Lakes and Warehouses, the industry is continually evolving to provide new and exciting technological solutions.
This webinar will help make sense of the various data architectures & technologies available, and how to leverage them for business value and success. A practical framework will be provided to generate โquick winsโ for your organization, while at the same time building towards a longer-term sustainable architecture. Case studies will also be provided to show how successful organizations have successfully built a data strategies to support their business goals.
Measuring Data Quality Return on InvestmentDATAVERSITY
ย
Data Quality is an elusive subject that can defy measurement and yet be critical enough to derail any project, strategic initiative, or even a company. The data layer of an organization is a critical component because it is so easy to ignore the quality of that data or to make overly optimistic assumptions about its efficacy. Having Data Quality as a focus is a business philosophy that aligns strategy, business culture, company information, and technology in order to manage data to the benefit of the enterprise. It is a competitive strategy.
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data ...DATAVERSITY
ย
Data can provide tremendous value to an organization in todayโs information-driven economy. New customer insights, better efficiency, and new product innovation are just some of the ways organizations are obtaining value through data. But in order to achieve this value, a strong data architecture is required to ensure that the data infrastructure runs smoothly, while at the same time aligning with business needs and corporate culture. A Data Strategy can assist in building a data architecture foundation through:
Identifying business requirements, rules & definitions via a business-centric data model
Creating a data inventory & integrating disparate data sources
Building a technical data architecture through data models & related artifacts
Coordinating the people, processes and culture necessary for success
Identifying tools & technology needed for creating & maintaining high quality data
DAS Slides: Building a Data Strategy - Practical Steps for Aligning with Busi...DATAVERSITY
ย
Developing a Data Strategy for your organization can seem like a daunting task. The opportunity in getting it right can be significant, however, as data drives many of the key initiatives in todayโs marketplace: digital transformation, marketing, customer centricity, and more. This webinar will help de-mystify Data Strategy and Data Architecture and will provide concrete, practical ways to get started.
ADV Slides: Databases vs Hadoop vs Cloud StorageDATAVERSITY
ย
Relational databases are old technology, right? Thirty years is a long time for a technology foundation to be as active as relational databases, but, like NFL coaches, we must โtolerate them until we can replace them.โ Are their replacements here? In this webinar, we say no.
Databases have not sat around while Hadoop emerged. The Hadoop era generated a ton of interest and confusion, but is it still relevant as organizations are deploying cloud storage options like a kid in a candy store? Weโll discuss Hadoopโs continued potential relevance and the cloud storage option that seems vital. Use what when? This is a critical decision that can dictate two to five times additional work effort if itโs a bad fit.
Drop the herd mentality. In reality, there is no โone size fits allโ right now. We need to make our platform decisions against this backdrop.
This webinar will distinguish these analytic deployment options and help you platform 2019 for success.
While many Digital Transformation initiatives are focused on improving the customer experience, often too little attention is paid to the customer-facing operational decisions that impact customers every day. To get the most from your Digital Transformation efforts, your customersโ experience and the decisions that impact it cannot be ignored.
Data is the lifeblood of just about every organization and functional area today. As businesses struggle to come to grips with the data flood, it is even more critical to focus on data as an asset that directly supports business imperatives as other organizational assets do. Organizations across most industries attempt to address data opportunities (e.g. Big Data) and data challenges (e.g. data quality) to enhance business unit performance. Unfortunately however, the results of these efforts frequently fall far below expectations due to haphazard approaches. Overall, poor organizational data management capabilities are the root cause of many of these failures. This webinar covers three lessons (illustrated by examples), which will help you to establish realistic OM plans and expectations, and help demonstrate the value of such actions to both internal and external decision makers.
Takeaways:
Organizational thinking must change: Value-added data management practices must be considered and included as a vital part of your business strategy.
Walk before you run with data focused initiatives: Understand and implement necessary data management prerequisites as a foundation, then build upon that foundation.
There are no silver bullets: Tools alone are not the answer. Specifying business requirements, business practices and data governance are almost always more important.
Data Governance โ Aligning Technical and Business ApproachesDATAVERSITY
ย
Data Governance can have a varied definition, depending on the audience. To many, data governance consists of committee meetings and stewardship roles. To others, it focuses on technical data management and controls. Holistic data governance combines both of these aspects, and a robust data architecture and associated diagrams can be the โglueโ that binds business and IT governance together. Join this webinar for practical tips and hands-on exercises for aligning data architecture & data governance for business and IT success.
Social media and relationship development for salesEconsultancy
ย
Econsultancy Director Peter Abraham's presentation on the topic of social media and relationship development for sales. (originally presented at Chicago Booth University School of Business)
Data Architecture Strategies: Data Architecture for Digital TransformationDATAVERSITY
ย
MDM, data quality, data architecture, and more. At the same time, combining these foundational data management approaches with other innovative techniques can help drive organizational change as well as technological transformation. This webinar will provide practical steps for creating a data foundation for effective digital transformation.
Modernizing the Enterprise Monolith: EQengineered Consulting Green PaperRachel Mezzatesta
ย
Are you an enterprise that recognizes the business liability inherent in the monolithic or otherwise dated enterprise software applications you have built? Does your technology represent an impediment to the needed agility and flexibility required to meet the needs of todayโs business environment?
Historically, enterprise software development focused on an approach that incorporated all functionality into a single process, and replicated it across servers as additional capacity was required. Today, these large applications have become bloated and unmanageable as new features and functionality are added. And, as small changes are made to existing functionality, the requirements to update and redeploy the server-side application becomes an intractable juggernaut.
Forward-thinking organizations like Amazon and Netflix led the way toward agile processes, deconstructed software stacks, and efficient APIs. Both large and small organizations serious about embracing modern practices have followed by decoupling the front and back end of their enterprise applications, employing microservices and cloud technologies, and adopting agile methodologies. These very steps can serve to highlight additional technical deficits in old solutions and codebases, which in turn become stumbling blocks to modern development practices.
As these technology trends continue to evolve, how can your company keep pace and remain viable?
In this green paper, we discuss how CIOs, CTOs, and VPs of Engineering can lead the needed modernization with their counterparts in marketing and the business to ensure that their organizations remain competitive in todayโs customer-driven and technology-led economy.
Key questions addressed include:
โข Why is technical modernization vital for the business?
โข What types of modernization projects are there?
โข How does modernization fit into your organization?
Modernizing the Enterprise Monolith: EQengineered Consulting Green PaperMark Hewitt
ย
Are you an enterprise that recognizes the business liability inherent in the monolithic or otherwise dated enterprise software applications you have built? Does your technology represent an impediment to the needed agility and flexibility required to meet the needs of todayโs business environment?
Historically, enterprise software development focused on an approach that incorporated all functionality into a single process, and replicated it across servers as additional capacity was required. Today, these large applications have become bloated and unmanageable as new features and functionality are added. And, as small changes are made to existing functionality, the requirements to update and redeploy the server-side application becomes an intractable juggernaut.
Forward-thinking organizations like Amazon and Netflix led the way toward agile processes, deconstructed software stacks, and efficient APIs. Both large and small organizations serious about embracing modern practices have followed by decoupling the front and back end of their enterprise applications, employing microservices and cloud technologies, and adopting agile methodologies. These very steps can serve to highlight additional technical deficits in old solutions and codebases, which in turn become stumbling blocks to modern development practices.
As these technology trends continue to evolve, how can your company keep pace and remain viable?
In this green paper, we discuss how CIOs, CTOs, and VPs of Engineering can lead the needed modernization with their counterparts in marketing and the business to ensure that their organizations remain competitive in todayโs customer-driven and technology-led economy.
Key questions addressed include:
โข Why is technical modernization vital for the business?
โข What types of modernization projects are there?
โข How does modernization fit into your organization?
Creating an Agile Enterprise ArchitectureCognizant
ย
With the proliferation of digital, the function of enterprise architecture is more critical than ever. Getting there requires a strong, agile enterprise architectural foundation that can embrace a fail-fast/fail-safe approach to the IT charter of stronger business alignment, while ensuring that services are delivered fast and friction-free to meet the needs of todayโs dynamic business objectives.
Aligning business and tech thru capabilities - A capstera thought paperSatyaIluri
ย
Enterprises the world over spend billions of dollars on technology enablement of business functions. A significant portion of those dollars end up creating suboptimal solutions. Most IT project problems are rooted in ambiguous business definition, churn in requirements gathering, scope creep beyond a minimum marketable feature set, wild cost guestimations, not planning for interdependencies, and a lack of strong governance.
This Capstera white paper seeks to address some of these problems and provide a framework to minimize the challenges.
DevOps shifting software engineering strategy Value based perspectiveiosrjce
ย
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Revolutionizing IT Project Delivery - Embrace the Future with OnePlanโs AI-Po...OnePlan Solutions
ย
IT departments are under increasing pressure to deliver projects that align with โ and also drive โ business strategy. But traditional Project Portfolio Management (PPM) simply canโt keep pace with the dynamic landscape of managing IT technology projects. Thatโs why we developed OnePlanโs AI-powered Strategic Portfolio and Work Management Platform.
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Embrace Modular Technology and Agile Process to Deliver Business Impact
1. Embrace Modular Technology
and Agile Process to
Deliver Business Impact
A Consulting Green Paper for CIOs, CTOs, CDOs,
CMOs, CFOs and CEOs
By Julian Flaks, Russ Harding and Mark Hewitt
2. 2 P.O. Box 211 Hampton Falls, NH 03844 | eqengineered.com | info@eqengineered.com | 617.448.4255
Green Paper versus White Paper
The term white paper originated with the British government, and many point to the Churchill
White Paper of 1922 as the earliest well-known example under this name.
White papers are a way the government can present policy preferences before it introduces
legislation. Publishing a white paper tests public opinion on controversial policy issues and
helps the government gauge its probable impact.
By contrast, green papers, which are issued much more frequently, are more open-ended.
Also known as consultation documents, green papers may merely propose a strategy to
implement in the details of other legislation, or they may set out proposals on which the
government wishes to obtain public views and opinion.
3. 3 P.O. Box 211 Hampton Falls, NH 03844 | eqengineered.com | info@eqengineered.com | 617.448.4255
Table of Contents
Why Read This Green Paper 4
Executive Summary 5
Introduction | Modularization Driving Agile Productivity 6
Modularization for Productivity Gains 7
Identify the Purpose 7
Types of Modularization 7
Language Level Modularization & Patterns 7
Layering with Software Frameworks 8
Message Based | Microservices 9
User Interfaces | Separate Module or Modules 10
Agile Productivity Supported by Modularization 10
Agile Process Delivered in Harmony with Architecture 11
Organization Strategy and Modularity 12
Security and Modularity 13
Development Operations and Agile 13
Conclusion 15
Take Aways 15
4. 4 P.O. Box 211 Hampton Falls, NH 03844 | eqengineered.com | info@eqengineered.com | 617.448.4255
Why Read This Green Paper
Is your enterprise technology built in a modular way? Can you modify or replace a component
without affecting other parts of the technology architecture? Is your technology platform built
with plug and play elements to allow for rapid change and adaptation to business and
customer forces? Do you employ Agile processes to make calculated changes incrementally?
Technology architecture and implementation governed by a coherent platform strategy that
prioritizes flexibility and component and service independence will deliver business impact.
In this paper, we articulate technology platform and architecture requirements to support
modern ways of delivering iterative value, increasing the velocity, productivity, and
performance of the organization, and reducing product and service time to market.
5. 5 P.O. Box 211 Hampton Falls, NH 03844 | eqengineered.com | info@eqengineered.com | 617.448.4255
Executive Summary
Modular technology platform architecture and Agile development are core elements of a
successful digital transformation in all organizations. Organizations need to focus on
continuous improvement and the currency of technologies to deliver business results for the
enterprise while inspiring a culture of learning for employees.
Digital transformation is the use of technology to radically improve the performance or reach
of an organization. In a truly digital business that is digitally enabled, new technologies enable
process improvement, talent engagement, and new business models.
-The Nine Elements of Digital Transformation, MIT Sloan Management Review
3 Core Components: Modularity of Platform, Technically Governed Agile, and
Organizational Empowerment
1. Efficiencies are derived from the technical platform. In technical teams, this means
iteratively improving productivity, performance and speed through modernization of the
technology utilized. Currency and modularity of the strategic asset of technology will
enable growth and the ability of the enterprise to compete and thrive. Modularity is the
backbone to an extensible architecture.
2. Architectural governance belongs inside Agile delivery. Architectural soundness is
an operational need, not a philosophical stance. The ability to incrementally improve
the whole without diluting the architecture allows Agile development practice in the
short term to align with technical goals in the long term. By adhering to higher
architectural constraints, Agile delivery can approach problems in a way that better
supports the long-term goals within feature focused sprints.
3. Organizational strategy is reflective of the need to support Agile with technical
readiness. Just as Agile adoption needed to be accompanied by an organizational
acceptance of the approach and the changes it brings, it is the organization as a whole
which needs to help make sure the technology is at a coherence, modernity, and
maturity where it can serve as the backdrop to productivity.
Insights
โข Architecture is a defined and documented understanding that encompasses
future change. The highest technical strategy must be planned and mindful, keeping
its shape despite Agile day-to-day delivery rather than being informed by it.
โข Change does not happen without leadership. Agile requires both organizational and
technical readiness to enable it to operate efficiently.
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Introduction | Modularization Driving Agile Productivity
Companies that are investing in technology architecture today are creating a strategic
advantage and a competitive differentiator for their businesses.
Enterprise architecture represents the vanguard
of modernization and digital transformation.
Organizations have largely moved to Agile methodologies. Agile productivity frameworks have
a track record of helping drive iterative value, as well as helping product development remain
focused on desirable product behavior.
However, the practice of sprint-based deliverables can be challenged by many commonplace
aspects of enterprise software, such as:
โข large, complex codebases,
โข older or fragmented technology stacks,
โข differing customer needs,
โข complex data needs, and
โข evolving understanding of product direction.
Compromised architecture and big technical problems are not the environment in which Agile
delivery thrives. Rather, they represent impediments which can reduce productivity and the
quality of the final product.
Modularization presents itself as a way forward through large-scale technical encumbrances
of a system. It can represent a cleaner delivery of functionality and help deployment options.
As a step to technical modernization, modularization can also be a pathway to help reduce
the risk of bringing portions of a product codebase forward in time while maintaining a
complete working system. And, modularity can help to enable the shift toward increased
leverage of cloud services.
The goal of modularity at the broadest level may be allied with a product strategy, wherein
individual components or portions of a platform may be combined in ways that make sense to
users. Formalizing the boundaries of service components within existing products may help to
increase the opportunities in the same way that outward facing APIs have allowed customers
to derive more diverse functionality from product offerings.
The acceptance of Agile methodology has come from the strategic and financial need to
accelerate product development to provide differentiation and excellence in experience.
Removing the obstacles to that delivery is a priority which must be taken seriously at the
organizational level.
7. 7 P.O. Box 211 Hampton Falls, NH 03844 | eqengineered.com | info@eqengineered.com | 617.448.4255
Modularization for Productivity Gains
Modularization may be described as breaking down a system into smaller component pieces
that are expected to carry out independent operations.
Modularization is a technique to divide a software system into multiple discrete and
independent modules, which are expected to be capable of carrying out task(s)
independently. -Tutorialpoint
Identify the Purpose
Modularity can improve various technical situations, and in its different ways may suit one
goal over another. If the modularity is to allow different versions of a framework or differing
frameworks, the underlying purpose of their co-existence will help to rationalize where
boundaries are split. If differing domain models make sense to divide, then again, a functional
division may be identified which is at odds with layering. On the other hand, if the modularity
is driven purely by a wish to remain scalable and to reduce the coupling between pieces to
allow easier upgrades, then infrastructural boundaries will likely be indicated.
In any event, the equation keeps the decision of modularizing in the language of the big
picture of productivity and planning for efficiencies. In turn, this helps modularity claim its
place in business level discussions and decision-making, and not be thought of as a technical
subtlety.
Types of Modularization
Language Level Modularization & Patterns
Modularization has helped drive programming language design since early generations of
language. The ability to break up methods into smaller units, and most significantly the
developments of object orientation and encapsulation behind interfaces, has helped to isolate
specifics in ways that allow for multiple implementations and later replacements to fit in
neatly. Type systems, which may complicate the modularization of builds, give this isolation a
semantically rich and meaningful contract. Microsoftโs .NET Common Language Runtime
allowed this strategy to be shared between multiple languages, as did later Java Virtual
Machine languages which took the ecosystem wider than just Java itself.
Beyond the languages, patterns emerged taking the benefits of modularity further, from
SOLID principles helping build stronger object orientation, to practices of layered architecture
which kept data access in its own place. Already these concerns tie in with some of the
business goals of modularization. Strong encapsulation and layering allow for platforms to
build up with a degree of isolation from feature-supporting code which relies on them.
Translated to Agile processes, this can mean the difference between an Agile team staying
safely inside its lanes while leveraging the best a platform can offer, and a team either having
8. 8 P.O. Box 211 Hampton Falls, NH 03844 | eqengineered.com | info@eqengineered.com | 617.448.4255
to tread cautiously because edits will inevitably affect many product areas at once, or
compromising layering altogether and creating new duplicative infrastructural code in various
places. In turn, compromises to layers will make the work exponentially harder when it comes
to upgrading or replacing an infrastructural concern since there may not be a single incision
point in the codebase.
Software build processes are also a target of focused modularity. A module depending on
another module in a build should not, in turn, be required by that module, as cyclic
dependencies at a minimum point toward undesirable coupling of module code. Build
engineering would seem a more localized concern than other topics of this paper, but in an
enterprise codebase, it is entirely common to find a compromised build where one module
will not build in isolation, even though the project is laid out in a modular way. In the day-to-
day work of a small, Agile sprint, this can translate to how long it takes for each single
developer to run tests against changes they make. Combined with modern source control
flows, with merges of many branches being a daily activity, the ability to test modular portions
of code can be critical to efficiency.
Layering with Software Frameworks
Frameworks grew in importance as enterprise code increasingly leveraged more off-the-shelf
code to handle functionality shared by all applications: database access, messaging, view
layer logic, serialization and so on. Frameworks play a big role in productivity, and good
experiences with various frameworks and languages caused a shift towards more framework-
oriented development. Depending on the underlying language as well as the design and
ecosystem of these, enterprise code would to a greater or lesser degree be decoupled from
the framework assumptions. As with language considerations, this is where some nuances
can end up playing a divisive role later.
An example is dependency injection. Since early in its history, the most popular Java
framework โ Spring - provided excellent support for dependency injection. At the same time,
Spring was also careful to follow Java community standards such that annotations applied to
a codebase to be acted on by Spring could also be understood by different frameworks
should an organization choose to go a different way. Likewise, the Java community arrived at
standards for persistence annotation, so that different Object Relational Mappers could be
plugged in without changing application code.
Furthering the example of dependency injection is Microsoftโs .NET offering. For a long time,
.NET has supported dependency injection through 3rd
party tools like AutoFac, Unity, and
Ninject, among others. Nonetheless, more recently with the release of .NET Core,
dependency injection has become a first-class citizen no longer requiring 3rd
party tools,
although they are still supported. The limit of frameworks that can be integrated, scoped, and
tested using dependency injection in .NET is limited only by the developerโs imagination and
the projectโs architectural needs. The abstractions now built into .NET make tasks such as
9. 9 P.O. Box 211 Hampton Falls, NH 03844 | eqengineered.com | info@eqengineered.com | 617.448.4255
Test-Driven Development (TDD), changes in business logic at runtime, or injecting logic
through middleware easy to develop, integrate and plug-and-play using well understood best
practices.
Not all frameworks are alike in this, and some software frameworks perceived as supportive
of productivity may provide poorly for upgrades, demanding many changes and targeting new
greenfield projects ahead of existing ones. Patterns adopted in application logic to work well
with a framework may translate clumsily into alternatives if they later need dropping in.
Stronger typed systems may make boundaries and encapsulations more obvious, while in
some dynamically typed code, replacing libraries or pieces of infrastructure may not present
their incompatibilities and complexities until the code is run.
Informed trade-offs need to be made, between maximizing the off-the-shelf efficiency of a
framework, and adding enough layered code to future proof change should a dependency
become legacy and unsupported. Project code complexity can be thought of as a measure of
how maintainable a codebase will be, so the adoption of software frameworks, while often a
practical necessity with benefits, has serious long-term implications.
Message Based | Microservices
With message-based systems and microservices, modularization entered a new phase.
Enterprise Service Bus architectures connected code via growing patterns of message
queues, adapters and listeners. Where this approach lived in a more prescriptive, specific
sector of software development, a broader definition of microservices became commonplace
across all types of server-side software development.
In place of language types, the encapsulation comes in the form of RESTful service endpoints
or in the defined semantics of the messages being published to persistent queues. A
particular note of caution is to be clear of the difference between data and the interface, as
complicated query parameters may cover validly variable shapes of data or equally may hide
a lack of clear API definition. The modularity gains from separated services can be skin deep
if detailed entrails of services are leaked to other services and opportunities missed for
stricter contracts.
One appeal of these systems is to reduce complexity within each service. Another benefit is
to allow for greater code differences between the various parts. For domains involving
specific code approaches such as machine learning, this polyglot approach can have appeal.
Even so, where the justifications are weak, deliberate fragmentation of a codebase can make
it harder to understand. Perhaps less glamorously, separation of code between services
allows different frameworks, and just as crucially, different versions of frameworks, to exist at
once in the same codebase. This will be discussed further in the Agile and Productivity
section.
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User Interfaces | Separate Module or Modules
User Interfaces may best be thought of as themselves being a good target of modularity.
Commonalities between the modeled concepts may be strong between the back end and
front end. Notwithstanding, this reliance is a big risk for both sides of the equation. User
experience has unique variables and considerations, along with changes in expectation and
best practice, and must be free to evolve outside the rest of the system.
Microservices on the back end may be split by user feature areas, by more generic layering of
infrastructure needs, or a combination of the two. Front end code does not need to follow the
same chosen separations. A single area of a single page application may communicate data
with various parts of the system whole; whether they do so via one or multiple entry-points is
a choice of implementation with nuanced implications.
Sometimes the choice of service boundaries will point towards data bottlenecks which will
affect user experience, and consideration will need to be given to whether the obstruction will
be soluble via some relaxation of the need for real-time reflection of data.
Outside of this, recognize that the UI will likely need refactoring and restructuring as users of
the application want different things, when UI or device trends change, or when frameworks
evolve in unexpected ways. The ability of a system to have a new front end or front ends
talking to the existing RESTful APIs represents perhaps the highest ROI of modularity in
a user-facing system.
Modularity may serve an important role in separating parts of the front end itself. Redux is an
example of layering working effectively in the front end, giving data its own space orthogonal
to page logic and layout code. Higher order components or complex services can be
examples of separating cross cutting concerns in JavaScript code in a way which helps a
clean approach. Nevertheless, the front end tends to be a domain where code organization
and clean sharing of functionality is still more challenging, and the benefits and costs of
approaches must be weighed carefully.
Agile Productivity Supported by Modularization
Agile methodologies prescribe a culture of continuous improvement, and Agile teams
generally grow in efficiency as they have the chance to refine how they work as a unit.
Velocity measurement can be a useful tool to help people understand when things have gone
better or worse. Even so, it should not be used as a goal or a metric by which the teamโs
performance is measured.
In the above discussion of microservice and message-based modularity, the notion of
services allowing differing frameworks or versions of frameworks existing side-by-side is
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explored. The significance of this to productivity and unhindered Agile sprints is that it allows
the isolation of legacy portions of application code which are more difficult to work with, as
well as to enable new features or versions of features to be built in more ideal, up to date
technology. The most outdated portions of an application may become a focus area of
specific developers, while other teams work outside of its constraints. By moving with the
times in a piecemeal way, there is the opportunity to limit accretion of outdated code,
something which often grows in anticipation of a later big-bang system upgrade.
One other advantage of Agile methodologies is that frequent delivery is encouraged. Both
technical and non-technical audiences alike โ be it the development teams or key business
stakeholders - benefit from the iterative delivery approach which fosters frequent
communication and confidently results in regular production releases. These periodic releases
reduce risk to the end user and provide a steady stream of improvement while simultaneously
returning valuable user data to the development team and business.
Agile Process Delivered in Harmony with Architecture
In this paper, the ways in which Modularization presents a number of different approaches to
escaping technical debt and empowering the Agile development process in ongoing feature
work have been discussed. There is a counter reality to this as well, namely that it is the role
of sound development processes to maintain that same extensible architecture as much as
possible.
Enlightened product owners will allow for some portion of sprints to undo architectural
damage caused by compromises of previous sprints, although this may often be less effective
than knowing how to avoid the compromise from the onset. There are times when speed of
delivery dictates a well understood and controlled technical debt accrual, yet often the
detrimental processes that undermine architecture are more hidden.
Consider the following scenario.
Sprint 1.
Product Owner: โI am including a story around an upcoming feature in this sprint.
Weโre not delivering this yet, but I know that there is an architectural problem, and I
want to give the team a chance to think about it.โ
Team: โWe discussed this, but the person who knows the most about this is out this
week, and there seems to be a solution so hopefully it is the right one.โ
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Sprint 2.
Product Owner: โThe spike was not conclusive last sprint, so I need us to deliver this
functionality this sprint.โ
Team: โThe person who knows the specifics of that area is back, but has limited time.
We chatted about it in a pull request. I am not sure we have time to change how we
have done this.โ
Sprint 3.
(A different team): โIt is a shame that other feature got implemented in the way it did.
We need to do something similar, but cannot follow the same pattern. And, now the
codebase is going to suffer from some confusion between the two approaches.โ
Reading the above realistic scenario assembled in summary form makes clear the need for an
architecture document. The very nature of Agile delivery is that it relies on team members
being empowered, having overlapping skill sets which allow work to continue without
becoming blocked by an individualโs expertise in a specific area. Formal statements of
architecture and guiding principles act to widen the pool of developers able to make
decisions that contribute to and maintain architectural integrity. Where Agile delivers small
bites of functionality, architecture is by its nature a big picture pillar.
While architectural plans and documents are of significant importance, the documents are not
necessarily the creation of a single or select group of developers. Rather, they represent
critical elements derived from decisions taken from a vantage point contemplating important
future considerations. The strategic questions which have recognized answers can be more
easily moved past in the course of ordinary sprint work once determined. Where questions
are reached for the first time, the architectural plan can grow and become refined.
By recognizing the strategic lines which different implementation details cross, it is easier for
a development team and product owner to more successfully choose when to take short-cuts
in the interest of immediate gain. In this way, the purely technical requirements needed to
keep the development machine running efficiently can be given a voice to compete with
pressing needs of functionality being delivered.
Organization Strategy and Modularity
The ways in which informed choices around modularity can play a vital role in helping the
effectiveness of software development has been explored. From an organizational viewpoint,
there are some ways in which teams can support the maintenance of well kept, modular
code, namely:
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โข Let the vocabulary of the most strategic elements of architecture permeate
conversations at high levels. Where costs must be incurred to arrive at an efficient
base level of technology, technology stakeholders need to understand the nature of the
investment.
โข Give recognition to infrastructural wins as well as to the more tangible and user-facing
achievements.
โข Product owners and platform owners must work in partnership. A product excelling in
its development cycles yet leaving the technology platform weaker as it does so, is a
short-term gain but a longer-term risk.
A healthy technical platform which has embraced service level modularity may also become
supportive of a mix-and-match product offering approach. Organizations may wish to deliver
offerings in new and innovative ways either to better support existing customers, or to appeal
to new categories of customers. Adapting technology to support such a requirement in the
short term can be limited in its success, and will often involve compromises in functionality,
design, maintainability, and speed of deployment. A technical platform whose boundaries are
readily understood should already provide a semantic backbone to allow modular solutions to
be designed and built.
Security and Modularity
It is a common experience in the enterprise for security concerns to be a prioritization which
waxes and wanes as threat awareness grows either internally or in the media. Beyond quick
fixes, software development can only promote security through the longer-term application of
best practices.
Modularization can help by encouraging the use of up-to-date technology, hiding older
technologies where necessary behind tightly confined boundaries, and keeping software
complexity in check. Still, the security strategy of a microservices system must be kept in
mind during all development, and its assumptions validated or invalidated as RESTful services
are designed. Simple definition of internal versus external facing endpoints, while useful,
should not preclude an application of defense-in-depth as it relates to modular components.
Development Operations and Agile
DevOps is an integral partner in enabling software frameworks, Agile methodologies, and
software modularity concepts to become a reality. DevOps enables improved security by
being the nexus between infrastructure and software teams enabling software to be delivered
reliably and automatically for the user of the application or system.
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Further, DevOps is a key partner in modular software, providing the tools and components to
deliver fit for purpose software components securely and at scale in an automated fashion.
When applied together Agile and DevOps better empower organizations to deliver technology
with greater speed and reliability, while simultaneously driving customer needs to the top of
the priority list.
Modern DevOps practices, in the cloud as well as in on-premise environments, help make
service-based modularity a practical reality. Tooling such as Docker allows developers to
explore and build complex multi-service environments within a single machine. In turn,
modularity which is well-thought out and documented can help to contain the complexity and
stability of the DevOps processes needed to support the platform.
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Conclusion
Modular technology platform architecture and Agile development are core elements of a
successful digital transformation in all organizations. Organizations need to focus on
continuous improvement and currency of technologies to deliver business results for the
enterprise while inspiring a culture of learning for employees.
Digital transformation is the use of technology to radically improve the performance or reach
of an organization. In a truly digital business that is digitally enabled, new technologies enable
process improvement, talent engagement, and new business models.
-The Nine Elements of Digital Transformation, MIT Sloan Management Review
Organizations that are successfully negotiating the needed modernization and technology
reengineering have leadership who recognize the need for growth in organizational
architecture, Agile adoption, and understanding across the business.
With this shift, enterprise architects and technologists are becoming more accountable for
solution outcomes and the need to increase technology and software development
productivity. They are also driving Agile adoption and speed to market to assist the enterprise
to grow, and mitigate future risks.
Take Aways
โข Technical architecture and development productivity have a symbiotic
relationship. The technical readiness of the platform is a force which has enormous
impact on Agile teams. The ability of those teams to achieve short term objectives
without hampering the effectiveness of the technical strategy is crucial.
โข Stakeholders in the output of Agile development are stakeholders in the
platform. The voice of the customer and product needs must be heard and will
naturally be a priority, while development with a view of the long-term extensibility of
the application will also enable the meeting of future customer needs.
โข Investing in technical readiness requires its own organization focus. The rewards
of a strong architecture and up-to-date technology are many, and will be supportive of
Agile efforts. In contrast to the more easily determined ROI of the development of
outward facing product functionality, the case for technical investment must ultimately
come from an organizational understanding of its importance.
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Authors
Julian Flaks โ CTO
Julian is a relentless problem solver and hoarder of full stack expertise. Having thrown
himself headlong into Internet technology when best practices had barely begun to
emerge, Julian is happiest putting his experience to use unlocking business value. Julian
holds a Bachelorโs of Laws from The University of Wolverhampton, England and a Master
of Science in Software Engineering from The University of Westminster.
Russ Harding โ Microsoft Practice Leader | Principal Consultant/Technical Architect
Russ specializes in providing technology leadership that inspires while bringing new ideas,
and technologies that result in high performance, high availability enterprise products. His
primary goal is always to improve efficiency and productivity for clients and bridge the
communication gap with leadership, team leads, project managers, and internal partners to
guarantee reliable and regular software delivery, and ensure an approach to development
that contributes to organizational goals and measurable business results.
Mark Hewitt โ President & CEO
Mark is a driven leader that thinks strategically and isnโt afraid to roll up his sleeves and get
to work. He believes collaboration, communication, and unwavering ethics are the
cornerstones of building and evolving leading teams. Prior to joining EQengineered, Mark
worked in various management and sales leadership capacities at companies including
Forrester Research, Collaborative Consulting, Cantina Consulting and Molecular | Isobar.
Mark is a graduate of the United States Military Academy and served in the US Army.