Continuous Intelligence (CI) integrates historical and real-time analytics to automatically monitor and update various types of systems, including supply chains, telecommunications networks and e-commerce sites. CI encompasses data ingestion, transformation and analytics, as well as operational “triggers” that recommend or initiate specific real-time actions.

CI casts a wider net than traditional analytics because it includes contextual data, for example related to market behavior, weather patterns or social media trends, that help enterprises operate the core systems more intelligently.

In this episode, our VP of Research Kevin Petrie interviews Simon Crosby, CTO at Swim.ai, a continuous intelligence software vendor that focuses on edge-based learning for fast-data. He co-founded security vendor Bromium in 2010, later sold to HP Inc in 2019.

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

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

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

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

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

This is an audio blog on BI on the Cloud Data Lake and how to improve the productivity of data engineers. We'll dive deeper into the question; what’s the best measure of success for data pipeline efficiency? This is part 2 of a two part blog.

Originally published at: https://www.eckerson.com/articles/business-intelligence-on-the-cloud-data-lake-part-2-improving-the-productivity-of-data-engineers

This audio blog is about business intelligence on the cloud data lake and why it arose and how to architect for it. This is Part 1 of a two part blog series.

Originally published at: https://www.eckerson.com/articles/business-intelligence-on-the-cloud-data-lake-part-1-why-it-arose-and-how-to-architect-for-it

This audio blog is about the data lakehouse and how it is the latest incantation from a handful of data lake providers to usurp the rapidly changing cloud data warehousing market. It is one of three blogs featured in the data lakehouse series.

Originally published at: https://www.eckerson.com/articles/all-hail-the-data-lakehouse-if-built-on-a-modern-data-warehouse

This is an audio blog about the perplexities of the Data Lakehouse and if it is, indeed, the "paradigm of the decade". To hear more of Eckerson Group perspectives on the data lakehouse be sure to check out the blogs from colleagues, Wayne Eckerson and Kevin Petrie, and the recording of our recent Shop Talk discussion.

Originally published at: https://www.eckerson.com/articles/an-architect-s-view-of-the-data-lakehouse-perplexity-and-perspective

This audio blog discusses the Data Lakehouse, a marketing concept that evokes clean PowerPoint imagery, and why and how the New Cloud Data Lake will play a very real role in modern enterprise environments.

Originally published at: https://www.eckerson.com/articles/data-lakehouses-hold-water-thanks-to-the-cloud-data-lake

This audio blog discusses cloud adoption and how data teams will migrate an increasing portion of their on-premises operational and analytics workloads to the cloud. They can best meet budget and project requirements by using data streaming technologies such as change data capture (CDC), which replicates real-time updates between data source and target.

Originally published at: https://www.eckerson.com/articles/the-next-wave-of-cloud-migrations-needs-data-streaming

This audio blog is about how the CHOP’s data and analytics (DnA) team uses near real-time data and information to decide how to marshal its resources to contain the pandemic. The culmination of all of this work has been an enterprise COVID-19 dashboard that is distributed to enterprise leadership daily. Originally published at: https://www.eckerson.com/articles/chop-harnesses-the-power-of-data-analytics-to-address-the-covid-19-pandemic

This audio blog is about the emerging concept of the data mesh and how enterprises are working tirelessly to centralize diverse, ever-multiplying datasets by transforming mountains of data they don’t understand, into information that analysts do understand. Originally published at: https://www.eckerson.com/articles/the-data-mesh-re-thinking-data-integration

As of this writing, billions of consumers live in quarantine. They buy what they need online, comforting themselves with food, TV, and toilet paper. Nobody is splurging at the mall.

To say the least, it is an interesting time to analyze discretionary consumer behavior. As Director of the Voice of Consumer Analytics at Adidas, Tiankai helps measure and manage the perception of a consumer brand that is mentioned on social media an average of 260,000 times per day. An amateur musician, Tiankai went viral himself lately with his series of “Quarantunes,” songs such as “Self Quarantine” and “Parent in Quarantine,” that poke fun at our homebound predicament.

Tiankai recently spoke with Eckerson Group about the art and science of consumer analytics, the COVID-19 conundrum, and (of course) the role of creativity in modern data analysis.

This audio blog focuses on data storytelling and how it uses numbers, narrative, and visuals to communicate insights that would otherwise be hard to absorb. Originally published at: https://www.eckerson.com/articles/data-storytelling-part-i-telling-it-like-it-is-and-was-and-will-be

This audio blog focuses on increase usage of NLP to navigate different formats, languages, terminologies, and biases and how this technology will help analyze the fast-growing body of research on COVID-19. Originally published at: https://www.eckerson.com/articles/how-covid-19-will-drive-adoption-of-natural-language-processing

Chief data officers (CDOs) first appeared in enterprise organizations after the Sarbanes Oxley Act became law in the United States in 2002 to improve corporate governance controls. CDOs started with a trickle, but have since become a flood, now populating more than two-thirds of large enterprises, according to a recent survey by NewVantage Partners.

To explore this dynamic role in detail, we invited Joe Dossantos, newly minted CDO for the data and analytics software vendor Qlik. Joe is responsible for data governance, internal data delivery, and self-service enablement. He also evangelizes data and analytics best practices to Qlik customers.

Prior to joining Qlik, Joe led TD Bank’s data strategy, and built and ran the Big Data Consulting Practice for EMC Corporation's Professional Services Organization.

A chief data officer not only defines a data strategy to meet current needs but also evolves the strategy to ensure that the organization derives value far into the future.

Originally published at https://www.eckerson.com/articles/seven-core-responsibilities-of-a-chief-data-officer-cdo

Data leaders who launch self-service analytics programs without knowing their business users risk unleashing chaos. Data leaders need to canvas the organization and understand who produces what information for whom and where.

Originally published at https://www.eckerson.com/articles/succeeding-with-self-service-analytics-know-thy-customer

Master Data Management is no shiny object. But like many traditional IT practices, MDM is being severely tested – and rendered all the more strategic – by digitalization and rising data volumes.

Originally published at https://www.eckerson.com/articles/five-master-data-management-best-practices-for-enterprises

The rise of machine learning has placed a premium on finding new sources of data to fuel predictive models. But acquiring external data is often expensive and many data sets are rife with errors and difficult to combine with internal data. But that’s going to change in 2020.

To help us understand the scale, scope, and dimensions of emerging data marketplaces is Justin Langseth, one of the visionaries in our space. Justin is a VP at Snowflake responsible for the Snowflake Data Exchange.  Prior to Snowflake, Justin was the technical founder and CEO/CTO of 5 data technology startups: Claraview (sold to Teradata), Zoomdata (sold to Logi Analytics), Clarabridge, Strategy.com, and Augaroo. He has 25 years of experience in business intelligence, natural language processing, big data, and AI.

Data quality and leadership trust levels may not seem connected, but they’re inextricably linked. Here’s why ...

Originally published at https://www.eckerson.com/articles/using-data-quality-to-build-trust-in-the-business-leaders

Data is critical for learning about the needs of the market, product bugs and issues, competitive solutions, and many other things. As such, analytics plays an important role in the innovation process.

Originally published at https://www.eckerson.com/articles/how-can-analytics-support-business-innovation

All organizations need to go down a similar path of data maturity. While you can skip steps in technology, you can’t skip steps in business data maturity.

Originally published at https://www.eckerson.com/articles/evolutionary-not-revolutionary-invest-less-in-new-tech-and-more-in-your-data-values