Businesses can leverage modern cloud platforms and practices for net-new solutions and to enhance existing capabilities, resulting in an upgrade in quality, increased speed-to-market, global deployment capability at scale, and improved cost transparency.
In this webinar, Josh Rachner, data practice lead at Sense Corp, will help prepare you for your analytics transformation and explore how to make the most on new platforms by:
Building a strong understanding of the rise, value, and direction of cloud analytics
Exploring the difference between modern and legacy systems, the Big Three technologies, and different implementation scenarios
Sharing the nine things you need to know as you reach for the clouds
You’ll leave with our pre-flight checklist to ensure your organization will achieve new heights.
Moving to the cloud in regulated environmentsKev Miller
Moving to the cloud in regulated environments - presentation by Astrix President, Dale Curtis at Lab Informatics Summit - details the process for moving from traditional premise-based lab tech to the cloud
Put Alternative Data to Use in Capital Markets Cloudera, Inc.
Alternative data for capital markets, such as satellite imagery, logistics data, and social media feeds, has been getting a lot of attention recently. Like any trending topic, its uses and benefits can be hyped up a bit but if the right plumbing and creativity is in place, those benefits can be realized.
3 things to learn:
* Examples of alt data use cases, sources, and recent market trends
* Why a big data platform that facilitates self service and collaboration is critical in monetizing alternative data
* How alternative data can be applied to enhance current processes (Demo)
Unlocking data science in the enterprise - with Oracle and ClouderaCloudera, Inc.
Today, leading organizations struggle to make their data scientists productive in their modern data platforms. Data scientists find it difficult to use their existing open source languages (e.g. Python, R) and libraries with Hadoop, especially when the clusters are secured with Kerberos. At the same time, IT doesn't want to give special access to these users, who require very diverse and specific environment configurations to run their experiments. As a result, most data science teams work away from the big data cluster, often on their laptops or in other data silos. The negative business impacts are a lack of insight and agility for the most advanced users, and the security, governance, and cost issues that arise from data silos.
The Big Picture: Real-time Data is Defining Intelligent OffersCloudera, Inc.
New research shows that 57% of the buying cycle is completed before a prospect even speaks to a company. Marketers already know this, Ninety-six percent (96%) of organizations believe that email personalization can improve email marketing performance. But where do we get this increasingly personal direction? The answer is likely in your customer data. In order to understand your customer needs contextualized in the moment they feel the need to act you will require a platform that can leverage real-time data. Apache Kudu is a Cloudera component that makes dealing with quickly changing data fast and easy. Companies are leveraging next generation data stores like Kudu to build data applications that deliver smart promotions, real-time offers, and personalized marketing. Join us as we discuss modern approaches to real-time application development and highlight key Cloudera use cases being powered by Cloudera’s operational database.
The CSC Big Data Analytics Insights service enables clients who do not have an analytics capability to implement the business, data and technology changes to gain business benefit from an initial set of analytics based on a roadmap of changes created by CSC or provided from a compatible set of inputs.
CSC Analytic Insights Implementation has four phases:
Stage 1: Analytic Engagement
Stage 2: Analytic Discovery
Stage 3: Implementation Planning
Stage 4: Embedding Analysis .
Get Started with Cloudera’s Cyber SolutionCloudera, Inc.
Cloudera empowers cybersecurity innovators to proactively secure the enterprise by accelerating threat detection, investigation, and response through machine learning and complete enterprise visibility. Cloudera’s cybersecurity solution, based on Apache Spot, enables anomaly detection, behavior analytics, and comprehensive access across all enterprise data using an open, scalable platform. But what’s the easiest way to get started?
Join Cloudera, StreamSets, and Arcadia Data as we show you first hand how we have made it easier to get your first use case up and running. During this session you will learn:
Signs you need Cloudera’s cybersecurity solution
How StreamSets can help increase enterprise visibility
Providing your security analyst the right context at the right time with modern visualizations
3 things to learn:
Signs you need Cloudera’s cybersecurity solution
How StreamSets can help increase enterprise visibility
Providing your security analyst the right context at the right time with modern visualizations
Moving to the cloud in regulated environmentsKev Miller
Moving to the cloud in regulated environments - presentation by Astrix President, Dale Curtis at Lab Informatics Summit - details the process for moving from traditional premise-based lab tech to the cloud
Put Alternative Data to Use in Capital Markets Cloudera, Inc.
Alternative data for capital markets, such as satellite imagery, logistics data, and social media feeds, has been getting a lot of attention recently. Like any trending topic, its uses and benefits can be hyped up a bit but if the right plumbing and creativity is in place, those benefits can be realized.
3 things to learn:
* Examples of alt data use cases, sources, and recent market trends
* Why a big data platform that facilitates self service and collaboration is critical in monetizing alternative data
* How alternative data can be applied to enhance current processes (Demo)
Unlocking data science in the enterprise - with Oracle and ClouderaCloudera, Inc.
Today, leading organizations struggle to make their data scientists productive in their modern data platforms. Data scientists find it difficult to use their existing open source languages (e.g. Python, R) and libraries with Hadoop, especially when the clusters are secured with Kerberos. At the same time, IT doesn't want to give special access to these users, who require very diverse and specific environment configurations to run their experiments. As a result, most data science teams work away from the big data cluster, often on their laptops or in other data silos. The negative business impacts are a lack of insight and agility for the most advanced users, and the security, governance, and cost issues that arise from data silos.
The Big Picture: Real-time Data is Defining Intelligent OffersCloudera, Inc.
New research shows that 57% of the buying cycle is completed before a prospect even speaks to a company. Marketers already know this, Ninety-six percent (96%) of organizations believe that email personalization can improve email marketing performance. But where do we get this increasingly personal direction? The answer is likely in your customer data. In order to understand your customer needs contextualized in the moment they feel the need to act you will require a platform that can leverage real-time data. Apache Kudu is a Cloudera component that makes dealing with quickly changing data fast and easy. Companies are leveraging next generation data stores like Kudu to build data applications that deliver smart promotions, real-time offers, and personalized marketing. Join us as we discuss modern approaches to real-time application development and highlight key Cloudera use cases being powered by Cloudera’s operational database.
The CSC Big Data Analytics Insights service enables clients who do not have an analytics capability to implement the business, data and technology changes to gain business benefit from an initial set of analytics based on a roadmap of changes created by CSC or provided from a compatible set of inputs.
CSC Analytic Insights Implementation has four phases:
Stage 1: Analytic Engagement
Stage 2: Analytic Discovery
Stage 3: Implementation Planning
Stage 4: Embedding Analysis .
Get Started with Cloudera’s Cyber SolutionCloudera, Inc.
Cloudera empowers cybersecurity innovators to proactively secure the enterprise by accelerating threat detection, investigation, and response through machine learning and complete enterprise visibility. Cloudera’s cybersecurity solution, based on Apache Spot, enables anomaly detection, behavior analytics, and comprehensive access across all enterprise data using an open, scalable platform. But what’s the easiest way to get started?
Join Cloudera, StreamSets, and Arcadia Data as we show you first hand how we have made it easier to get your first use case up and running. During this session you will learn:
Signs you need Cloudera’s cybersecurity solution
How StreamSets can help increase enterprise visibility
Providing your security analyst the right context at the right time with modern visualizations
3 things to learn:
Signs you need Cloudera’s cybersecurity solution
How StreamSets can help increase enterprise visibility
Providing your security analyst the right context at the right time with modern visualizations
Client approaches to successfully navigate through the big data stormIBM Analytics
Hadoop is not a platform for data integration: As a result, some organizations turn to hand coding for integration – or end up deploying solutions that aren’t fully scalable. Review this Slideshare to learn about IBM client best practices for Big Data Integration success.
Are You Prepared For The Future Of Data Technologies?Dell World
We are increasingly coming upon an age where technology is a strong enabler of business success, where there are strong synergies between business strategy and technology strategy. You often cannot discuss business strategy without data and related technologies being a big part of it. And as such, business leaders are increasingly turning to IT to compete more effectively in the market. As IT management, it falls upon you to ensure that your data technology architecture (software & hardware) is built in a way that it can handle the business demands of today and in to the future. In this session, we will discuss the various big data technology architectures and associated tools, and what role each should play in your data environment. We will also give real life examples of how others are using these technologies. Build a better data architecture, to unlock the power of all data.
Hadoop is regarded as a key capability for implementing Big Data initiatives in the enterprise, but organizations have yet to realize its full business benefits. In this webinar, Pivotal and guest Forrester Research, Inc. Identify the use cases driving Hadoop adoption, and explore what is needed to transform initial investments into results.
Learn about:
Challenges Hadoop introduces, and how the right tools and platforms can help address them
Shifts in the industry with regards to SQL and NoSQL systems and their implications to Big Data analytics
Applying in-memory technologies for data management systems, data analytics, transactional processing and operational databases
Watch the on-demand webinar here:
http://www.pivotal.io/big-data/pivotal-forrester-operationalizing-data-analytics-webinar
Learn how to maximize business value from all of your data here: http://www.pivotal.io/big-data/pivotal-hd
Becoming Data-Driven Through Cultural ChangeCloudera, Inc.
We've arrived at a crossroads. Big data is an initiative every business knows they should take on in order to evolve their business, but no one knows how to tackle the project.
This is the first in a series of webinars that describe how to break down the challenge into three major pieces: People, Process, and Technology. We'll discuss the industry trends around big data projects, the pitfalls with adopting a modern data strategy, and how to avoid them by building a culture of data-driven teams.
Sudhir Menon, Vice President of Enterprise Information Management on Hilton’s innovation/renovation journey to create data as an enterprise asset .The data framework using HortonWorks Hadoop as the platform is the single source and repository for any enterprise-class data for reporting, analytics and data science. To achieve this transformation and levarage data as a true enterprise asset, we focused on a roadmap with 3 major objectives:
• API based delivery of data enabling real-time use
• Decommissioning legacy tools/environments
• Managing the data architecture for all IT investments in a Big Data model with scalability over years
Platform and framework to accomplish this roadmap include:
• Repository of ‘master’ data
• Real-time processing of data for the enterprise
• Best-in-class BI tools to analyze and visualize data
• Data science tools to identify underlying trends in data
Our VISION
We enable travel & hospitality market disruption through data & analytics innovation
Our MISSION
We drive Hilton’s performance with actioned, integrated insights, through market-leading, differentiated expertise and continuous innovation.
Our STRATEGy
1. Create an aspirational and unrivaled hospitality Data & Analytics team that attracts the best talent
2. Become a trusted strategic business partner, driving untapped incremental value.
3. Provide timely access to quality data and innovative solutions.
Daniel is a Project Leader at Datayaan.
He has worked on designing and implementing innovative solutions for complex business problems and has helped companies with digital transformation.
Telehealth, Transport Logistics, and Telcom are some of the key areas his work covers.
And on the tech side he has widespread knowledge and experience in Microservices,IoT and Cloud.
He's going to talk about his approach in transforming an organization to leverage data-driven decision making.
For this he presents Transport Logistics as a use case and walks us through an overview of how the transformation takes place:
How the Data is Collected and Processed.. What we can do using the collected data.. and how the organization is benefitted..
He is also going to shed some light on how IoT can be used to automate data collection which is very crucial for building an effective data-driven business model
Ομιλία – Παρουσίαση: Katerina Nassou, HPE Pointnext Client Services
Τίτλος παρουσίασης: «Consumption based services to Accelerate your Digital Transformation»
Get ahead of the cloud or get left behindMatt Mandich
An enterprise cloud computing strategy results in:
Broad consensus on goals and expected results of moving select processes to the cloud
Standardized, consistent approach to evaluating the benefits and challenges of cloud projects
Clear requirements for the negotiation and monitoring of partnerships with cloud service providers
Understanding and consensus on the enabling and managing role IT will play in future cloud initiatives
Goals and a roadmap for transforming internal IT from asset managers to service broker
How Precisely and Splunk Can Help You Better Manage Your IBM Z and IBM i Envi...Precisely
Splunk, an industry leader in IT operations and security analytics, is moving to the cloud. Adopting Splunk in the cloud can help you make better, faster decisions with real-time visibility across the enterprise. That said, if your critical business services rely on the IBM Z or IBM i, including these systems is a must in your new Splunk environment.
Having these systems in your Splunk environment helps remove a significant blind spot in your modernization efforts - avoiding security risks, failed audits, downtime, and escalating costs.
Join this discussion with presenters Brady Moyer from Splunk and Ian Hartley from Precisely to learn how to seamlessly integrate IBM Z and IBM i into Splunk for a true enterprise-wide view of your IT landscape.
During this on-demand webinar, you will hear:
• How Precisely Ironstream provides integration with Splunk without the need for mainframe or IBM i expertise
• The different types of data that can be collected and forwarded to Splunk
• Example use cases for events, security, and performance data
Optimize your cloud strategy for machine learning and analyticsCloudera, Inc.
Join industry superstars Mike Olson (Cloudera CSO and co-founder) and Jim Curtis (451 Research senior analyst) as they outline the best practices for cloud-based machine learning and analytics in this “can’t miss” webinar.
Hot topics include:
Why enterprises are moving their analytics to the public cloud
How to select the best cloud deployment model
Design tricks that make cloud economics work
Success stories, cautionary tales, and lessons learned
James will share 451 Research findings and offer insights learned from surveying both the vendor landscape and enterprise practitioners.
.
Mike will regale you with his vision for the future of multi-disciplinary machine learning and analytics in hybrid- and multi-cloud environments
3 things to learn:
Why enterprises are moving their analytics to the public cloud
How to select the best cloud deployment model
Design tricks that make cloud economics work
MT13 - Keep your business processing operating at peak efficiency with Dell E...Dell EMC World
Big Data comes from somewhere! Chances are, the largest contributor to the data deluge in your world are your own main business processing systems. It’s critical to employ the highest efficiency possible when deploying Microsoft SQL, Oracle, or SAP database platforms for business processing. Join this session to find out more about Dell Engineered Solutions for Databases, and grow your data engines on your terms!
Data technology experts from Pivotal give the latest perspective on how big data analytics and applications are transforming organizations across industries.
This event provides an opportunity to learn about new developments in the rapidly-changing world of big data and understand best practices in creating Internet of Things (IoT) applications.
Learn more about the Pivotal Big Data Roadshow: http://pivotal.io/big-data/data-roadshow
MT101 Dell OCIO: Delivering data and analytics in real timeDell EMC World
Today’s business operations increasingly rely on sophisticated integration of data streaming across the enterprise. This requires an analytics ecosystem that is highly current and highly available. This session explores the infrastructure and methods Dell IT used for keeping the complex flows, integration processes, BI, and analytics operating 24x7.
Migrating to the Cloud – Is Application Performance Monitoring still required?eG Innovations
As more businesses adopt cloud technologies for their various benefits it must be noted that not all cloud offerings are the same and provide different services or infra SLA. Do you know that not all SLA from cloud providers mean your application will be ensured similar availability?
Depending on whether you are leveraging Saas, Paas, Iaas, etc to deliver your applications, you will have a different level of visibility and control of how you manage performance and deliver the user experience expected by your users.
Join the session and find out what remains within your responsibility and how you can monitor the various cloud infrastructure/services to give yourself the needed visibility to deliver the expected user experience without over-provisioning to ensure better performance.
[Infographic] Cloud Integration Drivers and Requirements in 2015SnapLogic
SnapLogic and TechValidate queried more than 100 U.S. companies with revenues greater than $500 million about the business and technical drivers and barriers for enterprise cloud application adoption in 2015 and beyond.
You can also learn how the SnapLogic Elastic Integration Platform can help by going to www.SnapLogic.com/iPaaS.
CSC - Presentation at Hortonworks Booth - Strata 2014Hortonworks
Come hear about how companies are kick-starting their big data projects without having to find good people, hire them, and get IT to prioritize it to get your project off the ground. Remove risk from your project, ensure scalability , and pay for just the nodes you use in a monthly utility pricing model. Worried about Data Governance, Security, want it in the cloud, can’t have it in the cloud….eliminate the hurdles with a fully managed service backed by CSC. Get your modern data architecture up and running in as little as 30 days with the Big Data Platform As A Service offering from CSC. Computer Science Corporation is a Certified Technology Partner of Hortonworks and is a Global System Integrator with over 80,000 employees globally.
Client approaches to successfully navigate through the big data stormIBM Analytics
Hadoop is not a platform for data integration: As a result, some organizations turn to hand coding for integration – or end up deploying solutions that aren’t fully scalable. Review this Slideshare to learn about IBM client best practices for Big Data Integration success.
Are You Prepared For The Future Of Data Technologies?Dell World
We are increasingly coming upon an age where technology is a strong enabler of business success, where there are strong synergies between business strategy and technology strategy. You often cannot discuss business strategy without data and related technologies being a big part of it. And as such, business leaders are increasingly turning to IT to compete more effectively in the market. As IT management, it falls upon you to ensure that your data technology architecture (software & hardware) is built in a way that it can handle the business demands of today and in to the future. In this session, we will discuss the various big data technology architectures and associated tools, and what role each should play in your data environment. We will also give real life examples of how others are using these technologies. Build a better data architecture, to unlock the power of all data.
Hadoop is regarded as a key capability for implementing Big Data initiatives in the enterprise, but organizations have yet to realize its full business benefits. In this webinar, Pivotal and guest Forrester Research, Inc. Identify the use cases driving Hadoop adoption, and explore what is needed to transform initial investments into results.
Learn about:
Challenges Hadoop introduces, and how the right tools and platforms can help address them
Shifts in the industry with regards to SQL and NoSQL systems and their implications to Big Data analytics
Applying in-memory technologies for data management systems, data analytics, transactional processing and operational databases
Watch the on-demand webinar here:
http://www.pivotal.io/big-data/pivotal-forrester-operationalizing-data-analytics-webinar
Learn how to maximize business value from all of your data here: http://www.pivotal.io/big-data/pivotal-hd
Becoming Data-Driven Through Cultural ChangeCloudera, Inc.
We've arrived at a crossroads. Big data is an initiative every business knows they should take on in order to evolve their business, but no one knows how to tackle the project.
This is the first in a series of webinars that describe how to break down the challenge into three major pieces: People, Process, and Technology. We'll discuss the industry trends around big data projects, the pitfalls with adopting a modern data strategy, and how to avoid them by building a culture of data-driven teams.
Sudhir Menon, Vice President of Enterprise Information Management on Hilton’s innovation/renovation journey to create data as an enterprise asset .The data framework using HortonWorks Hadoop as the platform is the single source and repository for any enterprise-class data for reporting, analytics and data science. To achieve this transformation and levarage data as a true enterprise asset, we focused on a roadmap with 3 major objectives:
• API based delivery of data enabling real-time use
• Decommissioning legacy tools/environments
• Managing the data architecture for all IT investments in a Big Data model with scalability over years
Platform and framework to accomplish this roadmap include:
• Repository of ‘master’ data
• Real-time processing of data for the enterprise
• Best-in-class BI tools to analyze and visualize data
• Data science tools to identify underlying trends in data
Our VISION
We enable travel & hospitality market disruption through data & analytics innovation
Our MISSION
We drive Hilton’s performance with actioned, integrated insights, through market-leading, differentiated expertise and continuous innovation.
Our STRATEGy
1. Create an aspirational and unrivaled hospitality Data & Analytics team that attracts the best talent
2. Become a trusted strategic business partner, driving untapped incremental value.
3. Provide timely access to quality data and innovative solutions.
Daniel is a Project Leader at Datayaan.
He has worked on designing and implementing innovative solutions for complex business problems and has helped companies with digital transformation.
Telehealth, Transport Logistics, and Telcom are some of the key areas his work covers.
And on the tech side he has widespread knowledge and experience in Microservices,IoT and Cloud.
He's going to talk about his approach in transforming an organization to leverage data-driven decision making.
For this he presents Transport Logistics as a use case and walks us through an overview of how the transformation takes place:
How the Data is Collected and Processed.. What we can do using the collected data.. and how the organization is benefitted..
He is also going to shed some light on how IoT can be used to automate data collection which is very crucial for building an effective data-driven business model
Ομιλία – Παρουσίαση: Katerina Nassou, HPE Pointnext Client Services
Τίτλος παρουσίασης: «Consumption based services to Accelerate your Digital Transformation»
Get ahead of the cloud or get left behindMatt Mandich
An enterprise cloud computing strategy results in:
Broad consensus on goals and expected results of moving select processes to the cloud
Standardized, consistent approach to evaluating the benefits and challenges of cloud projects
Clear requirements for the negotiation and monitoring of partnerships with cloud service providers
Understanding and consensus on the enabling and managing role IT will play in future cloud initiatives
Goals and a roadmap for transforming internal IT from asset managers to service broker
How Precisely and Splunk Can Help You Better Manage Your IBM Z and IBM i Envi...Precisely
Splunk, an industry leader in IT operations and security analytics, is moving to the cloud. Adopting Splunk in the cloud can help you make better, faster decisions with real-time visibility across the enterprise. That said, if your critical business services rely on the IBM Z or IBM i, including these systems is a must in your new Splunk environment.
Having these systems in your Splunk environment helps remove a significant blind spot in your modernization efforts - avoiding security risks, failed audits, downtime, and escalating costs.
Join this discussion with presenters Brady Moyer from Splunk and Ian Hartley from Precisely to learn how to seamlessly integrate IBM Z and IBM i into Splunk for a true enterprise-wide view of your IT landscape.
During this on-demand webinar, you will hear:
• How Precisely Ironstream provides integration with Splunk without the need for mainframe or IBM i expertise
• The different types of data that can be collected and forwarded to Splunk
• Example use cases for events, security, and performance data
Optimize your cloud strategy for machine learning and analyticsCloudera, Inc.
Join industry superstars Mike Olson (Cloudera CSO and co-founder) and Jim Curtis (451 Research senior analyst) as they outline the best practices for cloud-based machine learning and analytics in this “can’t miss” webinar.
Hot topics include:
Why enterprises are moving their analytics to the public cloud
How to select the best cloud deployment model
Design tricks that make cloud economics work
Success stories, cautionary tales, and lessons learned
James will share 451 Research findings and offer insights learned from surveying both the vendor landscape and enterprise practitioners.
.
Mike will regale you with his vision for the future of multi-disciplinary machine learning and analytics in hybrid- and multi-cloud environments
3 things to learn:
Why enterprises are moving their analytics to the public cloud
How to select the best cloud deployment model
Design tricks that make cloud economics work
MT13 - Keep your business processing operating at peak efficiency with Dell E...Dell EMC World
Big Data comes from somewhere! Chances are, the largest contributor to the data deluge in your world are your own main business processing systems. It’s critical to employ the highest efficiency possible when deploying Microsoft SQL, Oracle, or SAP database platforms for business processing. Join this session to find out more about Dell Engineered Solutions for Databases, and grow your data engines on your terms!
Data technology experts from Pivotal give the latest perspective on how big data analytics and applications are transforming organizations across industries.
This event provides an opportunity to learn about new developments in the rapidly-changing world of big data and understand best practices in creating Internet of Things (IoT) applications.
Learn more about the Pivotal Big Data Roadshow: http://pivotal.io/big-data/data-roadshow
MT101 Dell OCIO: Delivering data and analytics in real timeDell EMC World
Today’s business operations increasingly rely on sophisticated integration of data streaming across the enterprise. This requires an analytics ecosystem that is highly current and highly available. This session explores the infrastructure and methods Dell IT used for keeping the complex flows, integration processes, BI, and analytics operating 24x7.
Migrating to the Cloud – Is Application Performance Monitoring still required?eG Innovations
As more businesses adopt cloud technologies for their various benefits it must be noted that not all cloud offerings are the same and provide different services or infra SLA. Do you know that not all SLA from cloud providers mean your application will be ensured similar availability?
Depending on whether you are leveraging Saas, Paas, Iaas, etc to deliver your applications, you will have a different level of visibility and control of how you manage performance and deliver the user experience expected by your users.
Join the session and find out what remains within your responsibility and how you can monitor the various cloud infrastructure/services to give yourself the needed visibility to deliver the expected user experience without over-provisioning to ensure better performance.
[Infographic] Cloud Integration Drivers and Requirements in 2015SnapLogic
SnapLogic and TechValidate queried more than 100 U.S. companies with revenues greater than $500 million about the business and technical drivers and barriers for enterprise cloud application adoption in 2015 and beyond.
You can also learn how the SnapLogic Elastic Integration Platform can help by going to www.SnapLogic.com/iPaaS.
CSC - Presentation at Hortonworks Booth - Strata 2014Hortonworks
Come hear about how companies are kick-starting their big data projects without having to find good people, hire them, and get IT to prioritize it to get your project off the ground. Remove risk from your project, ensure scalability , and pay for just the nodes you use in a monthly utility pricing model. Worried about Data Governance, Security, want it in the cloud, can’t have it in the cloud….eliminate the hurdles with a fully managed service backed by CSC. Get your modern data architecture up and running in as little as 30 days with the Big Data Platform As A Service offering from CSC. Computer Science Corporation is a Certified Technology Partner of Hortonworks and is a Global System Integrator with over 80,000 employees globally.
This presentation will describe the analytics-to-cloud migration initiative underway at Fannie Mae. The goal of this effort is threefold: (1) build a sustainable process for data lake hydration on the cloud and (2) modernize the Fannie Mae enterprise data warehouse infrastructure and (3) retire Netezza.
Fannie Mae partnered with Impetus for modernization of its Netezza legacy analytics platform. This involved the use of the Impetus Workload Migration solution—a sophisticated translation engine that automated the migration of their complex Netezza stored procedures, shell and scheduler scripts to Apache Spark compatible scripts. This delivered substantial savings in time, effort and cost, while reducing overall project risk.
Included in the scope of the automation project was an automated assessment capability to perform detailed profiling of the current workloads. The output from the assessment stage was a data-driven offloading blueprint and roadmap for which workloads to migrate. A hybrid cloud-based big data solution was designed based on that. In addition to fulfilling the essential requirement of historical (and incremental) data migration and automated logic translation, the solution also recommends optimal storage formats for the data in the cloud, performing SCD Type 1 and Type 2 for mission-critical parameters and reloading the transformed data back for reporting/analytical consumption.
This will include the following topics:
i. Fannie Mae analytics overview
ii. Why cloud migration for analytics?
iii. Approach, major challenges, lessons learned
Speaker
Kevin Bates, Vice President for Enterprise Data Strategy Execution, Fannie Mae
Migrating Thousands of Workloads to AWS at Enterprise Scale – Chris Wegmann, ...Amazon Web Services
At the end of this session participants will learn how to assess their enterprise application portfolio and move thousands of instances to AWS in a quick and repeatable fashion. Migrating workloads to AWS in an enterprise environment is not easy, but with the right approach, an enterprise sized organization can migrate thousands of instances to AWS quickly and cost effectively to ensure a strong ROI.
Migrating to Cloud: Inhouse Hadoop to Databricks (3)Knoldus Inc.
Modernize your Enterprise Data Lake to Serverless Data Lake, where data, workloads, and orchestrations can be automatically migrated to the cloud-native infrastructure.
From Business Idea to Successful Delivery by Serhiy Haziyev & Olha Hrytsay, S...SoftServe
If you`ve missed SoftServe`s presentation on “Big Data Analytics Projects: From a Business Idea to a Successful Delivery” at the 2014 Data & Analytics Innovation and Entrepreneurship event in London or would like to refresh your memory, please download the full version of the presentation in the PDF format.
SoftServe`s renowned experts on BI and Big Data, Serhiy Haziyev and Olha Hrytsay, explored skills and experience required to avoid unpleasant pitfalls as well as practical recommendations on how to properly start a Big Data analytics project with a software development partner.
When and How Data Lakes Fit into a Modern Data ArchitectureDATAVERSITY
Whether to take data ingestion cycles off the ETL tool and the data warehouse or to facilitate competitive Data Science and building algorithms in the organization, the data lake – a place for unmodeled and vast data – will be provisioned widely in 2020.
Though it doesn’t have to be complicated, the data lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the data swamp, but not the data lake! The tool ecosystem is building up around the data lake and soon many will have a robust lake and data warehouse. We will discuss policy to keep them straight, send data to its best platform, and keep users’ confidence up in their data platforms.
Data lakes will be built in cloud object storage. We’ll discuss the options there as well.
Get this data point for your data lake journey.
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.
The coming years will be full of big changes in enterprise analytics and Data Architecture. William will kick off the fourth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
Global Data Management – a practical framework to rethinking enterprise, oper...DataWorks Summit
Global data management is not a newly coined term. However, what it stands for is actually widening in scope particularly around data-in-motion and data-at-rest. Significant technology trends such as IoT, cloud, AI/ML, blockchain, and streaming data have given rise to excessive data volumes and also innovative use cases. The scope for global data management now extends all the way from ingestion, processing, storage, governance, security to analysis. With a good number of endpoints served through the cloud and major application footprints remaining on-premisess, it is pertinent to have a global data management strategy that supports hybrid models and more specifically, a multi-cloud model.
Many modern businesses struggle to balance the demands of rapidly innovating through new technologies like machine learning with the need to keep data safe and secure, all while responding to a constantly changing regulatory landscape. This puts data stewards, data engineers, architects, data scientists, and analysts under intense pressure as they must contend with existing and new applications, multiple logical and physical data stores and sources, diverse data types, and data spread across several deployment environments.
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Speakers
Dinesh Chandrasekhar, Hortonworks, Director Product Marketing
Matt Aslett, 451 Research, Research Director, Data platforms and Analytics
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4. Reporting and dashboards evolve, and
Business Intelligence (BI) became the
phrase of the day.
In the marketplace, smaller BI vendors were
acquired by larger companies, while new
market entrants in this space conjured up
amazing data visualizations.
Organizations began leveraging cloud platforms
for data warehousing solutions by initially
deploying their data warehouse software on a
cloud infrastructure using hosted
environments.
The age of the internet yields larger volumes of
data. Organizations began using data
warehouse appliances for processing large
volumes of analytical data.
Organizations begin to evaluate true Data
Warehouse as a Service (DWaaS) solutions that
are fully operated and managed in the cloud.
Organizations are comfortable with having
Application Service Providers (ASPs) host and
maintain their data warehouse applications.
How modern analytics have developed over the years:
5. Months of setup
Primarily on-premises
Mainly structured SQL
Through custom APIs
Row-based; Clustering; Server processing
Batch; Built nightly
Managed by IT
Developed by developers
Days of setup
Data cloud and/or on-premises sources
Near real-time/real-time; Virtualized
Integrated with customer apps/self-service
Created by end users
Infrastructure
Data sources
Data types
Market data
Data storage
Processing
Aggregation
User interface
Visualization
Extract, Transform, Load (ETL); Schema write
Both structured and unstructured: SQL, XML, JSON, Avro,
Parquet, etc.
Extract, Load, Transform (ELT); Schema read
Column-based; Massively Parallel Processing (MPP);
In-Memory processing
Through marketplaces and data exchanges
Legacy Analytics Modern AnalyticsVS.
6. Increase speed
to market
Improve transparency
of costs
Deliver better analytics
service quality
Enhance security
Operate on a
global scale
Increase infrastructure
performance and
operating efficiency
Reduce data
center dependence
Strengthen DevOps
and DataOps
integration
Retain key personnel
and attract new hires
Assess Value Drivers that Fuel Your Journey
Create efficiency gains
9. 01
02
03
Big Data & AI/ML POCs and POVs
This is where organizations simply want to explore big data POC technical
feasibility or POV business capability solutions and use the modern analytics
platform to support rapid experimentation.
Migrating and Enhancing Legacy Analytics Solutions
This is where organizations want to move existing legacy analytics to a
modern analytics cloud platform to gain enhanced functionality. The effort is
driven by new data sources as well as trying to improve and enhance existing
analytics capabilities.
Licensing or Contractual Drivers
This is where organizations are battling heavy legacy environment
maintenance costs and wish to explore alternatives. For these organizations,
the primary driver is the requirement to move off the legacy platform as
soon as possible, allowing them to offset and reduce costs.
Value
Rapid experimentation and speed to market
Risk
Uncoordinated efforts can result in disjointed strategy
Value
Improved analytics capabilities with net new use cases
Risk
Ineffective migration strategy, failed/costly initiatives
Value
Use of cost-efficient cloud capabilities
Risk
Hidden cloud pricing can result in increased spend
Key Implementation Scenarios
11. 01. Cost & Complexity
Have you budgeted appropriately?
Have you planned for additional resources?
Have you planned for additional vendor management?
02. Hiring & Upskilling
Have you determined resource and skills needs?
Have you determined hiring or upskilling needs?
Have you created a training plan?
03. Budgeting & Procurement
Have you planned your CAPEX/OPEX shift?
Have you communicated the change to business units?
Have you developed an expense allocation plan?
04. Architecture Decisions
Have you determined your private/public needs?
Have you determined on-prem to cloud integration pipelines?
Have you factored in data and cyber security?
05. Migration Plans
Have you planned your migration?
Have you assessed your migration risks?
Have you aligned with the business?
06. Governance Change
Have you planned for real-time governance?
Have you considered master data integration?
Have you considered data virtualization?
07. Use Case Inventory
Have you appropriately developed your use case inventory?
Have you jointly developed use cases with the business units?
Have you balanced your use cases across value to the organization?
08. Technical Considerations
Have you documented your technical requirements?
Have you reviewed local, regional, and legislative considerations?
Have you evaluated the various technical options?
09. Security Decisions
Have you assessed and documented your security requirements?
Have you considered legislative constraints?
Have you evaluated the various security options?
The Modern Analytics Pre-Flight Checklist
12. Legacy Platform
Initial Investment
Modern Analytics
Projected Yearly Cost
Legacy Platform Yearly
Maintenance Cost
Figure 1: Yearly Cost Outlay
Modern Analytics
Legacy Analytics
Modern Analytics
Legacy Analytics
Legacy Platform
Initial Investment
Modern Analytics
Projected Yearly Cost
Legacy Platform Yearly
Maintenance Cost
This is where modern
analytics can cost more
than legacy analytics.
Modern Analytics
Projected Total Cost
Legacy Platform Total
Maintenance Cost
Figure 2: Total Cost Outlay
Modern Analytics
Legacy Analytics
Figure 3: Best Practice Total Cost Outlay
Modern Analytics
Projected Total Cost
Legacy Platform Total
Maintenance Cost
Legacy Platform
Initial Investment
Start small and
focus on AI/ML.
Generate value,
develop your
team, then
migrate
Modern Analytics
Projected Yearly Cost
Legacy Platform Yearly
Maintenance Cost
Assess Your Technology Cost Outlay
Legacy analytics is expensive up front and then usually decreases over time when paying annual maintenance fees.
Modern analytics can be expensive over time and needs to be managed effectively to ensure healthy cost of ownership.
13. Modern analytics platforms don’t require the typical infrastructure maintenance.
Scripts are needed to bring environments up and down. Environment upgrades are
performed by the vendor, which means infrastructure personnel need to be aware of
and understand the implications of environment changes.
Infrastructure Engineers
Data Engineers
Cloud Architect
Project/Cost Managers
Data Scientists
• Limited opportunity for upskilling; new
talent acquisition recommended
• Focus on scripting skills and automated
environment monitoring
• Acquire new talent
• Contract initially
• Build internal talent
• Upskill where possible
• Contract for best practices
• Acquire new talent
• Contract for best practices
• Use apprentice model
• Upskill where possible
• Leverage coding
• Support with training
Function
Is enhanced by this capability
The traditional ETL (extract, transform, load) data management and transformation
function is now different. The new platform requires extensive use of tools such as
Python. Those with traditional computer science and programming backgrounds are a
better fit.
Architecting cloud solutions is significantly different and better suited to those who
have been immersed in modern technologies and are familiar with big data
architectures and technologies.
Budgeting and managing costs on a modern platform require new skills to optimize
the pay-per-use model. Traditional project management will be limiting, and
practitioners need to learn and operate with Agile methodologies.
Creating solutions leveraging the modern analytics platform while using statistical
modeling requires a combination of math, programming, and domain expertise.
Description Talent Acquisition
Modern Analytics is a Team Sport
14. Modern Analytics = Financial Variability
Legacy Analytics
• Managed by IT
• Utilizes Established Cost Allocation Budgeting
• Capital Expenditure (CAPEX) Allocations
• Slower Response Time
• Low Financial Variability
Modern Analytics
• Managed by Business Units
• Requires New Real-Time Use Budgeting
• Operating Expenditure (OPEX)
• Faster Response Time
• High Financial Variability
Are you ready to handle the
financial variability as you
move from legacy analytics to
modern analytics?
15. User
Private Cloud
Public Cloud
• Private Front-End (Applications)
• Public Back-End (Data)
Private Front-End & Public Back-End
where data is routed through private
data centers with back-end
applications operating in the public
cloud.
01
User
Public Cloud
Private Cloud
• Public Front-End (Applications)
• Private Back-End (Data)
Public Front-End & Private Back-End
where public cloud technologies are
used to interface with the users, but
the data required is stored in a
private, secure cloud.
02
User
Public Cloud
Public Cloud
• Public Front-End and Back-End
(Applications & Data)
• Third-Party Add-on for Cyber
Security
Public Front & Back-End with Third
Party Add-Ons
where the public cloud solution is
integrated with additional
third-party add-ons for cybersecurity
and other requirements.
03
Prepare for Integration Complexity
16. Sunset: With some amount of work, it might be
possible to move the required functionality over into
other applications and use the opportunity to sunset
or retire older applications.
Lift and Shift: The simplest approach, especially
when faced with a time constraint, is to lift and shift
the application to the new environment. However,
this can result in neglecting the opportunity to
improve performance and enhance functionality. It
also means the problems with the legacy system can
be automatically inherited by the modern system.
Lift, Enhance, and Drop: This option involves the
core of an application being migrated as-is, but
also enhanced for performance improvement
and functionality to yield benefits where
applicable and possible.
Reimagine and Rebuild: In some cases, the application
might be outdated, or the new technology or
requirements are significantly different, and it might
be better to start from scratch and reimagine and
rebuild the application in a new way.
Migration Strategy of Critical Importance
17. ETL, APIs, EAI, ESB, etc.
Key data is replicated between legacy
analytics and modern analytics.
Applications and reporting systems
must source the data from each
environment.
Legacy
Analytics
Applications
Reporting &
Analytics
Reporting &
Analytics
Modern
Analytics
Applications Reporting &
Analytics
Reporting &
Analytics
Legacy
Analytics
Modern
Analytics
Virtual System Schema
Reporting &
Analytics
Reporting &
Analytics
Applications
Legacy
Analytics
Accelerated Data Warehouse
Technologies
Modern
Analytics
E.g.: Denodo, Composite, etc.
A single virtual system schema
becomes the primary source for data
needed by the various Applications
and reporting systems across the
organization.
E.g.: Incorta, Kyvos, etc.
Accelerated data warehouse technologies
can be used to deploy data warehouses
focusing on rapid development and
deployment leveraging newer “niche”
technologies.
“Hybrid” Data Mgmt. Strategy Inevitable
18. 70%of use cases should be able to
identify high-value initiatives
that will create change in the
organization
20%of use cases may be mundane,
but can be rapidly delivered
10%of use cases are edge cases
that feature AI, virtual reality
(VR), etc.
When evaluating modern analytics use cases,
we recommend the following:
• Explore small data analytics and obtain a
few quick wins before venturing into big
data analytics
• Ensure the use cases have strong business
ownership where involvement increases
the likelihood of success.
• Focus on use cases where you can
measure results and determine outcomes,
allowing you to drive meaningful change
and realize value derived from project
investment
• Target revenue generation use cases over
cost containment use cases.
Define Use Cases using ‘70/20/10 Model’
19. Regional
It may be important to evaluate where data centers are
located to pay special attention to high availability and
disaster recovery requirements.
01
Location
It may be necessary to ensure compliance with location-
based data residency legislation.
02
Control
It may be necessary to allow your administrators to have a
certain level of control over the management of
infrastructure and environments.
03
Technology
It may play a role in the selection of specific technologies
due to existing constraints (e.g. preferred alignment with
an existing technology vendor or movement toward the
use of open source technologies).
05
Vendor
Effective decision making may rely on evaluating and
understanding the vendor ecosystem and constraints (e.g.
recognizing vendor lock-in risks)
06
Tools
It may be important for administrators to understand what
the tools offer (e.g. environment ramp-up through coding
vs. configuration).
04
The What, Where, and How of Your Tech
20. Public Sector Regulation
Meeting government cloud (e.g.
CJIS, FedRAMP, etc.) needs
Hybrid Environments
Working with public and
private cloud environments
Encryption Keys
Setting up an encryption key
management system
Global Compliance
Ensuring compliance with GDPR
and other regulations
Access
Evaluating identity access
management (IAM) and single
sign-on (SSO)
Encryption Standards
Tracking approved vs. latest
encryption to match needs
Industry Compliance
Ensuring industry compliance
(e.g. HIPAA, ICD-10, PCI)
Audit Compliance
Reviewing the impact and risk
to business operations
Hardware Options
Evaluating hardware keys and
associated logistics
Security Requirements & Considerations
21. 01. Cost & Complexity
Have you budgeted appropriately?
Have you planned for additional resources?
Have you planned for additional vendor management?
02. Hiring & Upskilling
Have you determined resource and skills needs?
Have you determined hiring or upskilling needs?
Have you created a training plan?
03. Budgeting & Procurement
Have you planned your CAPEX/OPEX shift?
Have you communicated the change to business units?
Have you developed an expense allocation plan?
04. Architecture Decisions
Have you determined your private/public needs?
Have you determined on-prem to cloud integration pipelines?
Have you factored in data and cyber security?
05. Migration Plans
Have you planned your migration?
Have you assessed your migration risks?
Have you aligned with the business?
06. Governance Change
Have you planned for real-time governance?
Have you considered master data integration?
Have you considered data virtualization?
07. Use Case Inventory
Have you appropriately developed your use case inventory?
Have you jointly developed use cases with the business units?
Have you balanced your use cases across value to the organization?
08. Technical Considerations
Have you documented your technical requirements?
Have you reviewed local, regional, and legislative considerations?
Have you evaluated the various technical options?
09. Security Decisions
Have you assessed and documented your security requirements?
Have you considered legislative constraints?
Have you evaluated the various security options?
The Modern Analytics Pre-Flight Checklist
22. Thanks For Joining Us
We hope you enjoyed the presentation.
If you’d like to learn more about how to achieve new
heights with modern analytics, download our eBook.
https://sensecorp.com/achieve-new-heights-with-
modern-analytics/
DOWNLOAD EBOOK
www.sensecorp.com | marketing@sensecorp.com