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...
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 responsib...
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 ...
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
In this episode, Wayne Eckerson and Matthew Schwartz discuss non-traditional uses of business intelligence tools. Although BI tools have been around for almost three decades, most companies just scratch the surface of what’s possible to do with those tools. Using web layers and APIs, a company can use their imagination to customize and leverage their exiting BI tool-set to monetize data, integrate tribal knowledge and build industry-specific proprietary products. Matthew Schwartz is the chief te...
This audio blog probes the business value in analytics by examining the concept of Action Distance. Originally published at https://www.eckerson.com/articles/finding-value-in-analytics-action-distance
One of the hardest parts of running a data analytics program inside a large organization is governing data and reports. It’s simply too easy for the definition of core data elements and metrics to get out of sync and reports to contain conflicting information. Angie Davis has straddled both the business and IT worlds for more than 20 years. She served as a business analyst in several organizations before switching to the information technology side of the business where she ran analytics teams, ...
This audio blog focuses on the importance of establishing a strong relationship between business and technical teams and describes various business engagement models that sit at the heart of all successful data analytics programs.
Learn how to achieve the DataOps objectives of improved efficiency and data quality by migrating to a streaming architecture based on Apache Kafka.
Companies that excel at advanced analytics and data science maximize the value of their data. They unearth hidden opportunities and become innovators in the industry. Although each organization has different goals, the underlying processes and tools to become successful at analytics remain somewhat the same. In this episode, Alan Jacobson explains them one by one and finishes off with his top three recommendations. Alan Jacobson is the chief data and analytics officer (CDAO) of Alteryx, driving ...
With the growing popularity of machine learning and artificial intelligence, creating a data science program is a key initiative at most companies today. However, it’s not always clear to executives how they can deliver a return on investments in data science. To explain this, we invited an expert who has spent most of his career in the data science trenches and has a clear-minded perspective on how to deliver ROI with data science. Alan Jacobson is the chief data and analytics officer (CDAO) of...
How do you organize a data analytics program to maximize value for the organization? Although there is no right or wrong way to do this, several patterns emerge when you examine successful organizations. Originally published at https://www.eckerson.com/articles/organizing-for-success-part-ii-how-to-organize-a-data-analytics-program
Despite our reliance on reports, the state of reporting in most companies is awful. There are too many reports in too many locations created by too many different people and tools.
The goal of self-service analytics is to empower business people to build their own reports, dashboards, and predictive models. If that happens, does your company still need a corporate business intelligence team? Originally published at https://www.eckerson.com/articles/organizing-success-part-1-organize-bi-team
