The document provides findings from a survey of 150 data leaders about leveraging big data at their companies. Key findings include:
- Nearly all respondents believe their company is headed in the right direction with big data due to investments in new talent, technologies, and alignment on usage. However, only about half say big data is extensively leveraged across all business units currently.
- Respondents face challenges like data silos, legacy storage systems, and a lack of standardized measurement for big data initiatives. Finding skilled analytics talent is also difficult.
- Resources needed for success vary but include better tools, centralized talent management, and more information on the business value of big data.
COVID-19 has had a wide-ranging impact on the economy. Chisel Analytics surveyed over 100 leaders in analytics for their perspectives and the adjustments they're making in response.
Few decades ago, Managers relied on their instincts to take business decisions. They could afford to make mistakes and learn from it. Today, the scope for learning from mistakes is very minimal. Instincts should be backed by data to minimise mistakes.
Technological advancements, in addition to opening new channels of communication with customers, have also enabled organizations to collect vital information about their businesses with customers. But, have these organizations fully leveraged this data?
Today, Organizations make use of data for business decisions, but the data is not close enough to the customer to reap maximum benefit. In many cases, importance is not given to the granularity of data. The probability of “customer centric” decisions being right could be high, if the top management makes better use of the end user customer data (such as point of sale data, voice of customer, social media buzz etc.) to devise business strategies.
This report explores the road to big data adoption in Asia-Pacific. Asia-Pacific firms report limited success so far in implementing big data practices, however there is a strong appetite for an increased use of data analytics within their companies. Download full report on http://bit.ly/18Gzl0N
COVID-19 has had a wide-ranging impact on the economy. Chisel Analytics surveyed over 100 leaders in analytics for their perspectives and the adjustments they're making in response.
Few decades ago, Managers relied on their instincts to take business decisions. They could afford to make mistakes and learn from it. Today, the scope for learning from mistakes is very minimal. Instincts should be backed by data to minimise mistakes.
Technological advancements, in addition to opening new channels of communication with customers, have also enabled organizations to collect vital information about their businesses with customers. But, have these organizations fully leveraged this data?
Today, Organizations make use of data for business decisions, but the data is not close enough to the customer to reap maximum benefit. In many cases, importance is not given to the granularity of data. The probability of “customer centric” decisions being right could be high, if the top management makes better use of the end user customer data (such as point of sale data, voice of customer, social media buzz etc.) to devise business strategies.
This report explores the road to big data adoption in Asia-Pacific. Asia-Pacific firms report limited success so far in implementing big data practices, however there is a strong appetite for an increased use of data analytics within their companies. Download full report on http://bit.ly/18Gzl0N
Cracking the Data Conundrum: How Successful Companies Make #BigData OperationalSubrahmanyam KVJ
There is little arguing the benefits and disruptive potential of Big Data. However, many organizations have not fully embedded Big Data in their operations. In fact, our research shows that only 13% have achieved full-scale production for their Big Data implementations. The most troubling development is that most organizations are failing to benefit from their investments. Only 27% of respondents described their Big Data initiatives as “successful” and only 8% described them as “very successful”.
So, how can organizations make Big Data operational? There are many factors that go into the making of a successful Big Data implementation. However, the single biggest factor that we observed in our research was that organizations that have a strong operating model stood apart. This operating model has multiple distinct elements, which include, among others, a well-defined organizational structure, systematic implementation plan, and strong leadership support. For instance, success rates for organizations with an analytics business unit are nearly 2.5 times those that have ad-hoc, isolated teams. The report highlights the key factors for successful Big Data implementations.
These slides--based on the webinar hosted by leading IT analyst firm Enterprise Management Associates (EMA) and Digitate--provide insights into the impact of machine learning on managing workload automation.
Gramener is always on the lookout for talent who like to work with numbers and aspire to be the Algorithm Translators.
This deck is presented to cohorts at IIM's and other B School as part of Gramener company overview session.
Findings on health information technology and electronic health recordsDeloitte United States
The Deloitte Center for Health Solutions 2016 Survey of US Physicians set out to understand physician adoption and perception of key market trends around health information technology and electronic health record data. Explore key survey findings to discover where physicians find the most value, barriers to adoption, and what they want next. http://deloi.tt/2d3b4w6
Survey Results Age Of Unbounded Data June 03 10nhaque
Enterprises today can generate, collect and consider more data than ever before. New types of data can provide insight into previously opaque processes and motivations, but prodigious quantities of data present opportunity, as well as complexity and distraction. nGenera Insight’s 2010 Leading in an Age of Unbounded Data survey garnered responses from over 70 major organizations, including many global corporations, to provide a cross-industry pulse of the state of enterprise data.
Creating a Data-Driven Organization, Data Day Texas, January 2016Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
10 Steps to Develop a Data Literate WorkforceSense Corp
Gartner had predicted that by 2020, 80% of organizations would initiate deliberate competency development in the field of data literacy to overcome extreme deficiencies. This has become even more critical to businesses today as they seek to adjust to the remote settings of the COVID-19 pandemic.
Advanced data literacy makes an organization faster, smarter, and better prepared to succeed in a data-driven environment. However, many organizations struggle to create a data-literate workforce.
In this webinar, Alissa Schneider, Sense Corp data governance leader, will examine the fundamentals of data literacy, why it’s important in today’s marketplace, and share the 10 steps you can take to enhance the data literacy in your organization.
Contact us for more information: https://sensecorp.com/business-consulting-contact/
Data Trends for 2019: Extracting Value from DataPrecisely
To get the most business value from data, you need to keep up with the latest tech trends – or do you?
View this webinar on-demand as we share the results from our 2019 Data Trends Survey! We'll reveal what organizations around the world are really up to at the intersection of technology, big data and business.
Key topics include:
• Business initiatives getting the most IT support in 2019
• Highest-priority IT initiatives
• Tech adoption rates, benefits and challenges
This webinar was hosted by Gramener's CEO/Co-Founder, Anand S, and Ganes Kesari, Head of Analytics/Co-Founder on how data can help firms recover quickly throughout the recession and recovery period.
Who should watch this webinar :
Analytics Leaders, Business Leaders, CDOs, CTOs, etc.
Few takeaways :
-Which aspects of your company could benefit the most from a data-driven response?
-A strategy for identifying use cases that will provide the most value for the money.
How to use data in creative ways to uncover new market opportunities and customers.
Objectives :
-Data's utility in COVID situation
-How data science may assist you in navigating the recession
-Gramener's industry case studies to assist businesses in responding to COVID-19
Full Webinar: https://info.gramener.com/recession-proofing-your-business-with-data
To know more from industry leaders visit our official website: https://gramener.com/
Analytics is all about course correcting the future. While this starts with accurate predictions of the future, without resultant actions steering the future toward company goals, knowing that future is academic. Successful companies must be grounded in successful data-based prescription. In this webinar, William will present a data maturity model with a focus on how analytic competitors outdo the competition by looking forward to a data-influenced future.
Analytics Isn’t Enough To Create A Data–Driven CultureaNumak & Company
The earned values are perhaps compatible with older technologies. As we believe big data and AI are extensions of analytical capabilities, the most common and most likely to succeed are those related to "advanced analytics and better decisions."
Cracking the Data Conundrum: How Successful Companies Make #BigData OperationalSubrahmanyam KVJ
There is little arguing the benefits and disruptive potential of Big Data. However, many organizations have not fully embedded Big Data in their operations. In fact, our research shows that only 13% have achieved full-scale production for their Big Data implementations. The most troubling development is that most organizations are failing to benefit from their investments. Only 27% of respondents described their Big Data initiatives as “successful” and only 8% described them as “very successful”.
So, how can organizations make Big Data operational? There are many factors that go into the making of a successful Big Data implementation. However, the single biggest factor that we observed in our research was that organizations that have a strong operating model stood apart. This operating model has multiple distinct elements, which include, among others, a well-defined organizational structure, systematic implementation plan, and strong leadership support. For instance, success rates for organizations with an analytics business unit are nearly 2.5 times those that have ad-hoc, isolated teams. The report highlights the key factors for successful Big Data implementations.
These slides--based on the webinar hosted by leading IT analyst firm Enterprise Management Associates (EMA) and Digitate--provide insights into the impact of machine learning on managing workload automation.
Gramener is always on the lookout for talent who like to work with numbers and aspire to be the Algorithm Translators.
This deck is presented to cohorts at IIM's and other B School as part of Gramener company overview session.
Findings on health information technology and electronic health recordsDeloitte United States
The Deloitte Center for Health Solutions 2016 Survey of US Physicians set out to understand physician adoption and perception of key market trends around health information technology and electronic health record data. Explore key survey findings to discover where physicians find the most value, barriers to adoption, and what they want next. http://deloi.tt/2d3b4w6
Survey Results Age Of Unbounded Data June 03 10nhaque
Enterprises today can generate, collect and consider more data than ever before. New types of data can provide insight into previously opaque processes and motivations, but prodigious quantities of data present opportunity, as well as complexity and distraction. nGenera Insight’s 2010 Leading in an Age of Unbounded Data survey garnered responses from over 70 major organizations, including many global corporations, to provide a cross-industry pulse of the state of enterprise data.
Creating a Data-Driven Organization, Data Day Texas, January 2016Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
10 Steps to Develop a Data Literate WorkforceSense Corp
Gartner had predicted that by 2020, 80% of organizations would initiate deliberate competency development in the field of data literacy to overcome extreme deficiencies. This has become even more critical to businesses today as they seek to adjust to the remote settings of the COVID-19 pandemic.
Advanced data literacy makes an organization faster, smarter, and better prepared to succeed in a data-driven environment. However, many organizations struggle to create a data-literate workforce.
In this webinar, Alissa Schneider, Sense Corp data governance leader, will examine the fundamentals of data literacy, why it’s important in today’s marketplace, and share the 10 steps you can take to enhance the data literacy in your organization.
Contact us for more information: https://sensecorp.com/business-consulting-contact/
Data Trends for 2019: Extracting Value from DataPrecisely
To get the most business value from data, you need to keep up with the latest tech trends – or do you?
View this webinar on-demand as we share the results from our 2019 Data Trends Survey! We'll reveal what organizations around the world are really up to at the intersection of technology, big data and business.
Key topics include:
• Business initiatives getting the most IT support in 2019
• Highest-priority IT initiatives
• Tech adoption rates, benefits and challenges
This webinar was hosted by Gramener's CEO/Co-Founder, Anand S, and Ganes Kesari, Head of Analytics/Co-Founder on how data can help firms recover quickly throughout the recession and recovery period.
Who should watch this webinar :
Analytics Leaders, Business Leaders, CDOs, CTOs, etc.
Few takeaways :
-Which aspects of your company could benefit the most from a data-driven response?
-A strategy for identifying use cases that will provide the most value for the money.
How to use data in creative ways to uncover new market opportunities and customers.
Objectives :
-Data's utility in COVID situation
-How data science may assist you in navigating the recession
-Gramener's industry case studies to assist businesses in responding to COVID-19
Full Webinar: https://info.gramener.com/recession-proofing-your-business-with-data
To know more from industry leaders visit our official website: https://gramener.com/
Analytics is all about course correcting the future. While this starts with accurate predictions of the future, without resultant actions steering the future toward company goals, knowing that future is academic. Successful companies must be grounded in successful data-based prescription. In this webinar, William will present a data maturity model with a focus on how analytic competitors outdo the competition by looking forward to a data-influenced future.
Analytics Isn’t Enough To Create A Data–Driven CultureaNumak & Company
The earned values are perhaps compatible with older technologies. As we believe big data and AI are extensions of analytical capabilities, the most common and most likely to succeed are those related to "advanced analytics and better decisions."
Lead Your Data Revolution - How to Build a Foundation of Trust and Data Gover...DATAVERSITY
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<p>Becoming a data-driven organization is something many companies aspire to, but few are able to obtain. Let’s face it: Data is confusing. It is complicated, dirty, and spread out all over a business. While companies are making big investments in Data Management projects, only a few are seeing the payoff. </p>
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<p>New research from Experian shows that despite many ongoing data initiatives, 69 percent of organizations struggle to be data-driven. The struggles are real. Companies face a large data debt, look at data projects through a siloed lens, and still have a large volume of inaccurate data. In fact, 65 percent report inaccurate data is undermining key initiatives. <br></p>
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<p>However, the tide is turning. Businesses are starting to adopt data enablement, or a practice of empowering a larger group of individuals within the business to understand and harness the power of data and analytics. Companies that empower wider data usage are better able to comply with regulations, improve decision-making, and, of course, deliver a superior customer experience. Are these the results you’re striving for? </p>
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<p>Join us to uncover new research from more than 500 Data Management practitioners as we take a deep dive into:</p>
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<ul><li>The top challenges in becoming a data-driven organization </li><li>Trends and the rise of data enablement </li><li>The profile of a mature organization </li><li>Tips for how you can adopt data enablement practices</li></ul>
<!-- /wp:list -->
Cracking the Data Conundrum: How Successful Companies Make #BigData OperationalCapgemini
There is little arguing the benefits and disruptive potential of Big Data. However, many organizations have not fully embedded Big Data in their operations. In fact, our research shows that only 13% have achieved full-scale production for their Big Data implementations. The most troubling development is that most organizations are failing to benefit from their investments. Only 27% of respondents described their Big Data initiatives as “successful” and only 8% described them as “very successful”.
So, how can organizations make Big Data operational? There are many factors that go into the making of a successful Big Data implementation. However, the single biggest factor that we observed in our research was that organizations that have a strong operating model stood apart. This operating model has multiple distinct elements, which include, among others, a well-defined organizational structure, systematic implementation plan, and strong leadership support. For instance, success rates for organizations with an analytics business unit are nearly 2.5 times those that have ad-hoc, isolated teams. The report highlights the key factors for successful Big Data implementations.
How organizations can become data-driven: three main rulesAndrea Gigli
The presentation shows how organization can successfully become data driven and avoid wasting time and money. It explain how to prioritize business questtions, how to combine properly people, tech&data and processes, and how to structure a transforamtional journey for becoming a data driven.
Big Data and Analytics: The New Underpinning for Supply Chain Success? - 17 F...Lora Cecere
Executive Overview
Today data is everywhere: but, nowhere. The world’s per capita capacity to store information has doubled every 40 months since the 1980s; and as of 2012, every day globally, 2.5 exabytes of data are created . As a result, social and customer data piles on the doorstep of the corporation, and operational data sits in the creases and cracks between functions. While many companies invested in data warehouse technologies and advanced applications for optimization, a common complaint in qualitative interviews with business leaders is “I cannot get to my data.” One business leader likened it to a Hotel California where, “The data checks into the system, but does not check out.” In most companies with heterogeneous information technology landscapes, simple reporting is still a major problem.
In the face of growing data, companies struggle with the basics. The question is, “Why pursue a big data and analytics strategy if the company cannot do basis reporting?” No doubt about it, the current state of analytics is a barrier to building supply chain excellence. It is hard to have a data-driven discussion if you can’t get access to data.
Data democratization the key to future proofing data culturePolestarsolutions
Learn how to empower your organization with accessible data insights through democratizing your data. This guide offers tips for choosing the right tools and fostering a data-driven culture.
Data Literacy and Data Virtualization: A Step-by-step Guide to Bolstering You...Denodo
Watch full webinar here: https://bit.ly/2KLc1dE
An organization’s effectiveness can only be as good as the understanding of their data. Hence it is important for both the frontline workers as well as the managers to be data literate, so that they can they understand how the business is functioning, decide if any changes need to be made, and quickly make decisions to realize better outcomes. However, successful data literacy requires stringent processes and an effective tool to operationalize them.
Listen to the our replay on the 10-steps to building a data-literate organization, and how data virtualization can help implement the underpinning processes.
Sense Corp and Denodo have partnered to combine state-of-the art professional services with the industry’s most advanced data virtualization platform to streamline data access in support of the most critical business needs.
Watch the replay to learn:
- The 10-steps to data literacy; what you can do to become a high performer.
- How to use data virtualization as the foundation to implementing data literacy processes.
- Examples of companies that have achieved high levels of data literacy.
Download the Sense Corp 10 Steps to Data Literacy eBook to learn more.
You had a strategy. You were executing it. You were then side-swiped by COVID, spending countless cycles blocking and tackling. It is now time to step back onto your path.
CCG is holding a workshop to help you update your roadmap and get your team back on track and review how Microsoft Azure Solutions can be leveraged to build a strong foundation for governed data insights.
The world around us is changing. Data is embedded in everything, and users from all lines of business want to leverage this data to influence decisions. The trick is to create a culture for pervasive analytics and empower the business to use data everywhere.
The core enabling technology to make this happen is Apache Hadoop. By leveraging Hadoop, organizations of all sizes and across all industries are making business models more predictable, and creating significant competitive advantages using big data.
Join Cloudera and Forrester to learn:
- What we mean by pervasive analytics, how it impacts your organization, and how to get started
- How leading organizations are using pervasive analytics for competitive advantage
- How Cloudera’s extensive partner ecosystem complements your strategy, helping deliver results faster
Enabling Success With Big Data - Driven Talent AcquisitionDavid Bernstein
Adopting an evidence-based recruitment marketing strategy is not just reserved for large employers. In fact, a targeted sourcing strategy can in some ways have a greater impact on small and mid-size businesses who need to allocate already-limited resources to the areas that will provide the most value. Ultimately, hiring the right candidate means profitability for your business. How can talent acquisition professionals gain the insights their organizations need to make better-informed decisions about their recruitment marketing efforts?
This whitepaper from IBM shows how your organisation can implement a Big Data Analytics solution effectively and leverage insights that can transform your business.
The data management procedure employed by your firm is capable of building your brand or breaking it all over. So, be wise in choosing the right strategy.
Building an Effective Data Management StrategyHarley Capewell
In June 2013, Experian hosted a Data
Management Summit in London, with over
100 delegates from the public, private and
third sectors. Speakers from Experian
and across the data industry explored the
challenges of developing and implementing
data quality strategies - and how to
overcome them. Read on for more information.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
2. Methodology
We conducted a 10-minute online survey among n = 150 individuals in data-related roles. The survey was fielded from April
21st- May 5th, 2016.
Audience Definition Sample Size
Data
Leaders
• Work in companies with at least 5,000 employees
• Director-level or above
• Has influence over decisions to leverage big data to inform company business
decisions
• Has influence over decision to partner with business intelligence and big data
software vendors
• Works in a role related to:
o Big Data
o Data Strategy
o Data Management
o Data Integration
o Compliance/ Risk
o Analytics
o Business Intelligence
N=150
2
3. 3
Executive Summary
• Virtually all big data leaders are optimistic that their companies are headed in the right direction when it comes to leveraging big data efficiently—
their companies are dedicating new talent and tools to big data initiatives, and also gaining internal alignment around how big data will be used.
• Companies with big data leaders “very” or “extremely” successful at leveraging big data to make business decisions—however, nearly all plan to
continue investing in resources dedicated to big data and only 51% say their company leverages big data extensively, across all business units.
• The challenges data leaders’ companies face are wide-ranging, but companies have the most room for improvement when it comes to the tools
and technologies dedicated to big data and most respondents say that internal bottlenecks between the information technology and business units
prevent data from being accessed quickly and efficiently.
Key challenges data leaders face include:
o “Shadow analytics” leading to data governance problems
o Business users spending more time gathering data than performing analysis
o Legacy data storage systems requiring too much processing to meet today’s business requirements
o Too heavy a reliance on manual methods when prepping data
• There are a wide-range of resources companies need to leverage big data include better tools, more centralized talent and more information on why
leveraging big data is valuable.
4. 4
We first explored the extent to which data
leaders’ companies are leveraging big data
today and their outlook for the future
5. Nearly all respondents believe that their company is headed in the right direction
when it comes to leveraging big data efficiently
Headed in the right directionOff on the wrong track
Q2: When it comes to leveraging big data efficiently, do you believe your company is headed
in the right direction or off on the wrong track?
94%6%
5
6. Respondents cite more investment in new talent and technologies, and further
alignment on big data operations as the key reasons they are optimistic
Investing in Talent Investing in New Technologies Aligning on Big Data
“We hired
professionals with
proven experience in
this area.”
Q3: Why do you say your company is headed in the right direction when it comes to
leveraging big data efficiently?
“We have added
many servers and a
highly functioning
system with many
ways to protect
data/information.”
“Advanced data
software options give
us an edge in the
market place.”
“Our company is
starting to truly
understand the gains
that can be had using
big data. It will be a
priority going
forward.”
“We have many new skilled
workers in our company
who have a great deal of
experience dealing with
traffic commerce and this
frees up any clusters in our
data flow.”
“We are getting the right
parties involved in
addressing this. All too
often, IT goes off on their
own way due to the lack of
assistance from the line of
business units.”
“We have started pilot
programs in certain
departments to see how
big data can inform our
decisions and will use
the results to formulate
a broader strategy.”
6
7. Virtually all respondents say their company encourages its employees to ground
business decisions in data and evidence
60%
38%
2%
Strongly encouraged
Somewhat encouraged
Not encouraged
Q13: To what extent is it encouraged at your company for employees to ground business
decisions in data and evidence?
7
8. Perceptions of success are high, although less than one-quarter believe they are
“extremely successful”
23%
39%
30%
8%
0%
Extremely successful Very successful Somewhat successful Not very successful Not at all successful
Q1: How successful do you believe your company is at leveraging big data to make business
decisions today?
8
9. Despite today’s success, nearly all believe that their company’s investment in big data
resources will increase in the next five years
81%
8%
11%
Investment will increase
Investment will decrease
Investment will stay the same
Q14: How do you believe your company’s investment in resources (e.g., talent, tools and
technologies) to help leverage big data will change in the next five years?
9
10. 10
We gauged where respondents’ companies stand when it comes to three key
components of leveraging big data
Talent TechnologiesProcess
11. 2% 7% 13% 35% 43%
Most respondents (78%) work at companies where there is a member of the C-Suite
responsible for driving their ability to compete on analytics
Q7: Which of the following best describes your company when it comes to the talent it dedicates to managing big data?
My company has one member of the C-
Suite responsible for driving our ability
to compete on analytics; this leader
works seamlessly with other members
of the C-Suite
My company has one
member of the C-Suite
responsible for driving our
ability to compete on
analytics who works
independently to
determine how big data
will be used
My company does not have a
member of the C-Suite
responsible for driving
analytics but has a centralized
team with responsibility for
managing big data across
company functions
My company does not
have a member of the C-
Suite responsible for
driving analytics but some
company divisions employ
talent dedicated to
managing their big data
My company has not
yet employed any
talent exclusively
dedicated to
managing big data
Least Mature Most Mature
Talent Spectrum
Shortened statements used
11
12. 3% 7% 13% 41% 36%
Most respondents (64%) say that bottlenecks prevent big data from being accessed
quickly and efficiently
Q8: Which of the following best describes your company when it comes to how big data is accessed and shared across divisions?
There is a set process for accessing and
sharing big data across divisions at my
company and this process is widely
understood; no bottlenecks exist for
accessing data quickly and efficiently
There is a set process for accessing
and sharing big data across
divisions at my company that is
widely understood across divisions;
however, bottlenecks prevent big
data from being accessed quickly
and efficiently
There is a set process for
accessing and sharing big data
across divisions at my
company, but this process is
not widely understood across
divisions due to the
bottlenecks that exist
Although big data can be
accessed and shared
across divisions at my
company, there is no set
process for doing so as
there are too many
bottlenecks
Bottlenecks at my
company make it
impossible for big
data to be accessed
and shared across
divisions
Least Mature Most Mature
Process Spectrum
Shortened statements used
12
13. 1% 5% 23% 31% 39%
In nearly one-third of respondents’ companies, divisions do not have complete
visibility into data across all big data sources
Q9: Which of the following best describes your company when it comes to the tools and technologies it dedicates to organizing and leveraging big data?
My company uses effective tools to
organize and provide complete visibility
into all big data sources across divisions,
including structured and unstructured
data
My company uses effective tools to
organize and provide complete
visibility into all big data sources
across divisions, including
structured data; today, we do not
have tools to organize and provide
visibility into unstructured data
My company uses tools to
organize big data sources
across divisions, but the
limitations of the tools means
we cannot organize big data
effectively and do not have
complete visibility into all big
data sources
My company does not use
tools to organize big data
across divisions, but some
divisions have their own
tools to organize big data
My company does
not use any tools
to organize big
data today
Least Mature Most Mature
Technology Spectrum
Shortened statements used
13
14. 1% 5% 23% 31% 39%
Respondents are “least mature” when it comes to the technology dedicated to big
data
Least Mature Most Mature
3% 7% 13% 41% 36%
2% 7% 13% 35% 43%
People
Process
Technology
Shortened statements
14
15. Ultimately, only half of data leaders say that big data is leveraged extensively in their
company, throughout all business units
51%
34%
13%
2% 1%
Big data is leveraged
extensively, throughout all
business units / operations
Big data is leveraged regularly,
but only in some business units
/ operations
Big data is occasionally
leveraged, in a few select cases
My company has not yet
implemented processes to
leverage big data, but plans to
in the future
My company has not yet
implemented processes to
leverage big data, and has no
plans to in the future
Q4: Which of the following best describes your company today when it comes to big data to
inform business decisions?
15
17. Although most data leaders believe their companies are making a sufficient effort to
leverage big data, a subset say they are not doing enough
69%31%
Making a sufficient effortNot doing enough
Q12: Thinking about your company’s big data management practices, do you think leadership is making
a sufficient effort to leverage big data when making business decisions or are they not doing enough?
17
18. Respondents report needing better technology, fewer silos between departments, and
more internal buy-in to enable their company to more efficiently leverage big data
Better Technology Fewer Silos Between Departments More Internal Buy-In
Q18. What do you believe would enable your company to more efficiently leverage big data
to make business decisions?
“It boils down to
investments in software
and getting all systems
on the same platform
across the company.”
“Better collaboration
between units. We are
very siloed. I think we
need a comprehensive
standardization of how
we leverage big data.”
“More cross-functional
collaboration.”
“Strategic changes from
the top around
utilization and
implementation of big
data resources.”
“Having board members
better understand the
scope of what we are trying
to accomplish.”
“A general push from
upper management to
ramp up our efforts to
manage, aggregate, and
analyze big data would
be a good first step.”
“More text based data
needs to be utilized and the
manual excel spreadsheets
need to be eliminated in
favor of more automated
analytical software that will
sort the data more
effectively.”
18
19. Though respondents are optimistic about their ability to leverage big data, few are using
all their data in making business decisions
19%
26%
32%
17%
6%
0%-25% 26%- 50% 51%-75% 76%-90% 91%-100%
Q10: What percent of all the data collected by your company do you think
your company is analyzing and utilizing today to make business decisions?
Only 23% of respondents utilize
over three-quarters of their
available big data
19
20. . . . and accessing disparate data sources can frequently take a day or longer
Q11: How long does it generally take business users at your company to access disparate big
data sources for a single analysis?
11%
27%
24%
19%
10%
5% 4%
A few
minutes
Under an
hour
A few hours About 24
hours
About one
week or less
About two to
four weeks
More than
four weeks
37% say it takes one day or more to
access big data sources for an analysis
20
21. 49%
42%
28%
17%
17%
14%
66%
59%
42%
Finding and hiring skilled big data analytics
talent is difficult
The value of analytics is understood, but
not being quantified and articulated
adequately enough to secure buy-in
Ad hoc data analysis is not widely used
and valued in our organization
Somewhat agree Strongly agree
Q16: To what extent do you agree that each of the following factors are challenges your company faces in leveraging big data efficiently?
People Challenges
When it comes to the “people” needed for success, finding and hiring skilled big data
analytics talent is a major challenge
21
22. 40% 39% 35% 33% 29% 25%
19% 20%
17%
15%
17%
19%
59% 59%
52%
49% 45% 44%
“Shadow analytics”
leads to data governance
problems
Business users spend
more time gathering
data than performing
analysis
A great deal of our data
is not being incorporated
into analytics projects
today
Company-wide big data,
data is not put into the
hands of the right
business leaders
Data is siloed and
difficult to find and
leverage
It is not clear to
stakeholders across the
company what big data
is available and to whom
Somewhat agree Strongly agree
The biggest challenges around “process” concern data governance and business users
spending too much time gathering data vs. analysis
Shortened statements
Q16: To what extent do you agree that each of the following factors are challenges your company faces in leveraging big data efficiently?
Process Challenges
22
23. Respondents are split on whether big data is easily accessed or siloed within functions
59%41%
Unit leaders can easily access big data, and
it is easy for them to use the data to help
make business decisions quickly
Data is siloed within functions and it is
difficult for unit leaders to access the big
data they need when they need it
Q17: Which of the following best describes your company today when it comes to big data management?
23
24. 35% 33% 31% 34%
22%
24%
15% 17% 13%
11%
59%
48% 48% 47%
33%
Our legacy data storage
systems require too much
processing to meet today’s
business requirements
There is no standard way the
company measures success of
big data initiatives
There is too heavy a reliance
on manual methods and trial-
and-error when preparing
data
We do not leverage enough
text-based content for
analytics
We can’t trust that our data is
accurate and up-to-date
Somewhat agree Strongly agree
The main technology challenge data leaders face is legacy data storage systems
requiring too much processing to meet today’s business requirements
Q16: To what extent do you agree that each of the following factors are challenges your company faces in leveraging big data efficiently?
Technology Challenges
24
25. Only one-fifth of data leaders are “extremely satisfied” with the resources their
company dedicates to big data
Q6: What resources (e.g., talent, tools and technologies) do you believe
your company would need to be more successful when it comes to
organizing big data and leveraging it to make business decisions?
Q5: How satisfied are you with the resources (e.g., talent, tools and
technologies) your company currently devotes to organizing big
data and leveraging it to make business decisions?
[Showing “extremely satisfied”]
20%
“We need to scale up our use of
big data once the pilots are done,
which will mean hiring more
talent and giving the tools and
technology to more people.”
“A more defined mission
statement developed and
implemented by talented staff
using the proper technology.”
“To start off with, I would like to
see an increase to the members
of the team who are responsible
for Big Data Capture and Analysis.
They are a bit understaffed to
meet current needs. Two to Three
people with the right training
would make a big difference.”
25
26. Responses are fragmented when it comes to the resources needed—there is no one
area where big data analytics is “perfect”
42% 46% 45% 49% 35% 46% 38% 36% 39%
35% 31% 32% 26% 40% 29% 37% 37% 21%
77% 77% 77% 75% 75% 75% 75% 73%
60%
Providing more
information on how
big data can help
our company reach
business goals
Providing a better
understanding of
what big data my
company collects
Providing tools that
allow us to leverage
text-based
content—such as
email, social media,
and customer
support notes—for
analytics
Employing
centralized talent to
manage big data
utilization across
functions
Employing more
agile data
management
systems and
software to
organize big data
Providing evidence
proving how big
data has enabled
better business
decisions
Aligning internally
on who is
responsible for
utilizing big data
Providing a “one-
stop-shop” solution
for employees
across functions to
easily access and
use big data
Hiring a Chief Data
Officer (CDO) or
other C-suite data
analytics leader
Somewhat agree Strongly agree
Q19: To what extent do you agree that each of the following would enable your company to more
efficiently leverage big data to make business decisions?
• Respondents are most likely to “strongly agree” that employing more agile data management systems to organize
big data would enable their company to more efficiently leverage big data
26
27. Looking to the future, respondents agree big data will become more easily accessed
Q20: Thinking to the future of leveraging big data to make business decisions, to what extent do you
agree that each of the following statements will be true in 3 years?
[Showing % who strongly + somewhat agree]
27
67% 64% 63% 61%
The analytic skills necessary to
leverage big data to make
business decisions will be just as
common as word processing
skills are today
Every employee, regardless of
business unit, will be able to
efficiently leverage big data
when making business decisions
that are relevant to their job
The Chief Data Officer will be the
driver of organizational
effectiveness and competitive
success at large companies
Finding and using the correct
data will be as easy as running a
typical Google search
29. 29
Full statement Shortened Statement
People
Finding and hiring skilled big data analytics talent is difficult Finding and hiring skilled big data analytics talent is difficult
The value of analytics is understood, but not being quantified and articulated adequately
enough to secure buy-in
The value of analytics is understood, but not being quantified and articulated adequately
enough to secure buy-in
Ad hoc data analysis is not widely used and valued in our organization Ad hoc data analysis is not widely used and valued in our organization
Process
Data is siloed and difficult to find and leverage — the right data is not easily accessible to
those who need it
Data is siloed and difficult to find and leverage
It is not clear to stakeholders across the company what big data is available and to whom It is not clear to stakeholders across the company what big data is available and to whom
A great deal of our data is not being incorporated into analytics projects today, leaving us
with a partial business view
A great deal of our data is not being incorporated into analytics projects today, leaving us
with a partial business view
“Shadow analytics” – where business users perform analytics in Excel spreadsheets - leads
to data governance problems
“Shadow analytics” leads to data governance problems
Business users spend more time gathering data to analyze than performing actual analysis Business users spend more time gathering data to analyze than performing actual analysis
Although my company’s information technology group stores and secures company-wide
big data, data is not put into the hands of the right business leaders needed to leverage it
to make business decisions and create value.
Company-wide big data, data is not put into the hands of the right business leaders
Tools & Technology
There is no standard way the company measures success of big data initiatives There is no standard way the company measures success of big data initiatives
There is too heavy a reliance on manual methods and trial-and-error when preparing data
for analytics
There is too heavy a reliance on manual methods and trial-and-error when preparing data
We can’t trust that our data is accurate and up-to-date We can’t trust that our data is accurate and up-to-date
Our legacy data storage systems require too much up-front processing to meet today’s
business requirements
Our legacy data storage systems require too much processing to meet today’s business
requirements
We do not leverage enough text-based content – such as email, social media, customer
support notes – for analytics
We do not leverage enough text-based content for analytics
Challenges: Full and Shortened Statements