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Data Lake

COVID, inflation, broken supply chains, and not-so-distant war make this a turbulent time for the modern consumer. During times like these, families tend to their nests, which leads to lots of home-improvement projects…which means lots of painting.

Today we explore the case study of a Fortune 500 producer of the paints and stains that coat many households, consumer products, and even mechanical vehicles. While business expands, this company needs to carefully align the records that track hundreds of suppliers, thousands of storefronts, and millions of customers.

Business expansion and complex supply chains make it particularly important—and challenging—for enterprises such as this paint producer, which we’ll call Bright Colors, to accurately describe the entities that make up their business. They need to be governed, validated data to describe entities such as their products, locations, and customers. Master data management, also known as MDM, streamlines operations and assists data governance by reconciling disparate data records into golden records and ideally a single source of truth.

We’re excited to share our conversation with an industry expert that helps Bright Colors and other Fortune 2000 enterprises navigate turbulent times with effective strategies for MDM and data governance.

Dave Wilkinson is chief technology officer with D3Clarity, a global strategy and implementation services firm that seeks to ensure digital certainty, security, and trust. D3Clarity is a partner of Semarchy, whose Intelligent Data Hub software helps enterprises govern and manage master data, reference data, data quality, enrichment, and workflows. Semarchy sponsored this podcast.

Dave Wilkinson: Enterprise Data Governance and MDM Case Study

We in the West have watched Russia's invasion of Ukraine with disbelief and horror. How could this happen to a European country in the 21st century? Is there any justifiable rationale for the wanton destruction of people and property there? As we ponder these questions, our data colleagues in Ukraine have experienced the war firsthand. 

To help us get a handle on Ukraine's role in the data economy and how teams based there are coping with Russia's military onslaught, Wayne interviews two software executives today who share how the war has affected their companies and how they are adapting to the evolving situation. 

Dragos Georgescu is vice president and chief technology officer of DataClarity, an innovative data analytics vendor with a development shop in Lviv, Ukraine. 

Bogdan Steblyanko is CEO of CHI Software, a  software development company based in Ukraine with more than 500 employees spread across four development centers, including hard-hit Kharkiv in the east, which is the company's headquarters.

The Impact of the War in Ukraine on Data Teams

O’Reilly’s Mac Slocum talks with Edd Dumbbell, VP of strategy at Silicon Valley Data Science, about the data lake, the opportunities the model presents, and the driving forces behind the concept. In the second segment, O’Reilly’s big data guru Ben Lorica chats with Rajiv Maheswaran, CEO of SecondSpectrum, about spatial-temporal pattern recognition — what Maheswaran calls “the science of moving dots.”

The data lake model is a powerhouse for invention

Building a Data Lake in AWS - Mick Bass and Carla Cole - 47Lining

In this podcast episode, O’Reilly’s Shannon Cutt talks with Damon Feldman, solutions director at MarkLogic, a company that has developed an operational and transactional NoSQL database that integrates data silos to give customers a single view of their data. They discuss data lakes, data hubs, integrating data in a lake format, data governance related to security, and more.

Damon Feldman on Combining a Data Hub and Data Lake

In this episode of the O’Reilly podcast, I speak with Han Yang, senior product manager at Cisco, working on analytics solutions. We discuss the impact of data analytics across industries, building data lifecycles for Internet of Things (IoT) applications, and advice for establishing successful analytics and machine learning projects.

Building Data Lifecycles for IoT Projects With Edge Analytics

In this episode, Wayne Eckerson and Jeff Magnusson discuss a self-service model for data science work and the role of a data platform in that environment. Magnusson also talks about Flotilla, a new open source API that makes it easy for data scientists to execute tasks on the data platform. 

Magnusson is the vice president of data platform at Stitch Fix. He leads a team responsible for building the data platform that supports the company's team of 80+ data scientists, as well as other business users. That platform is designed to facilitate self-service among data scientists and promote velocity and innovation that differentiate Stitch Fix in the marketplace. Before Stitch Fix, Magnusson managed the data platform architecture team at Netflix where he helped design and open source many of the components of the Hadoop-based infrastructure and big data platform.

Jeff Magnusson: How To Create A Self-Service Data Platform For Data Scientists

In this podcast, Wayne Eckerson and James Serra discuss myths of modern data management. Some of the myths discussed include 'all you need is a data lake', 'the data warehouse is dead', 'we don’t need OLAP cubes anymore', 'cloud is too expensive and latency is too slow', 'you should always use a NoSQL product over a RDBMS.'

Serra is big data and data warehousing solutions architect at Microsoft with over thirty years of IT experience. He is a popular blogger and speaker and has presented at dozens of Microsoft PASS and other events. Prior to Microsoft, Serra was an independent data warehousing and business intelligence architect and developer.

James Serra: Myths of Modern Data Management

This EG blog is about data modernization steps and guiding principles that can help maintain balance within schools, stores, and other face to face businesses affected by COVID-19. 

Originally published at: https://www.eckerson.com/articles/covid-19-and-higher-education-a-case-study-in-data-modernization

COVID-19 and Higher Education: A Case Study in Data Modernization - Audio Blog

This blog is about the challenge of data sprawl and how the combination of AI-based entity matching, schema matching, and enhanced knowledge graphing is moving us ever closer to the vision of self-driving data.

Originally published at: https://www.eckerson.com/articles/using-data-knowledge-to-conquer-data-sprawl

Using Data Knowledge to Conquer Data Sprawl - Audio Blog

This blog is about Graphics Processing Units (GPU) and how much of the focus and industry growth in the use of GPUs has come from their suitability for machine learning, especially neural networks, more commonly known as deep learning. 

Originally published at: https://www.eckerson.com/articles/gpu-databases-getting-more-value-from-your-machine-learning-infrastructure

GPU Databases: Getting more Value from your Machine Learning Infrastructure - Audio Blog

This blog is about Continuous Intelligence (CI) and how it integrates historical and real-time analytics to operate, monitor and tune systems of all types. Our next blogs will explore architectural approaches to CI, and how to navigate the trade offs it introduces to your organization.

Originally published at: https://www.eckerson.com/articles/continuous-intelligence-the-nexus-of-data-integration-analytics-and-operations

Continuous Intelligence: the Nexus of Data Integration, Analytics and Operations - Audio Blog

This blog compares Predictive vs Prognostic analytics and gives a quick view into systems dynamics and causal modeling. If it sparks your interest, watch for an upcoming series of articles connecting the practices of systems thinking, causal analysis, and analytics.

Originally published at: https://www.eckerson.com/articles/looking-at-the-future-through-analytics-predictive-vs-prognostic

Looking at the Future through Analytics: Predictive vs. Prognostic - Audio Blog

Listen to data and analytics leaders share the secrets of their success. Wayne Eckerson, long-time global thought leader interviews guests who run data and analytics programs at Fortune 2000 organizations around the world. Tune in to stay abreast of the latest technologies, techniques, and trends in our fast-paced industry.

Jeff Magnusson: How To Create A Self-Service Data Platform For Data Scientists

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