Discover best practices to scale Power BI effectively—improving performance, governance, and self-service across enterprise environments. Published at: https://datalere.com/articles/power-bi-best-practices-from-the-field-lessons-from-enterprise-deployments

This blog defines conversational BI, why companies should consider it, and how their power and casual users can best get the desired results. Published at: https://www.eckerson.com/articles/driving-results-with-conversational-bi-best-practices-for-power-and-casual-users

Explore our four primary criteria for evaluating conversational BI products. Published at: https://www.eckerson.com/articles/genai-driven-analytics-product-evaluation-criteria-for-conversational-bi

It's not easy being the head of data & analytics at a large organization. You must align a large team across multiple disciplines; you must deal with oodles of legacy systems and tools that hamper innovation; and you must deliver business value fast to keep executives at bay and your job intact. You also need to recruit dynamic managers who can push the envelope while meeting operational objectives. And when you falter--which you inevitably will-you have to rebound fast.

No one knows these lessons better than Tiffany Perkins-Munn. She currently runs a 275-person data & analytics team at JP Morgan Chase that consists of data engineers, data scientists, behavioral economists, and business intelligence experts. She thrives on versatility, having earned a Ph.D. in Social-Personality Psychology with an interdisciplinary focus on Advanced Quantitative Methods. Building on this foundation, she has accumulated vast experience in the art of managing data & analytics teams during her 23 years in technical and managerial roles in the financial services industry.

In this interview, you’ll learn:

1. Tiffany’s secret for aligning a large data & analytics team and keep them from splitting into silos of specialization
2. Her favorite techniques for recruiting the right people to her team.
3. How to wade through the thicket of legacy systems and deliver innovative solutions quickly.
4. The impact of GenAI on her operations and the financial services industry.
5. How to advance your careers in data & analytics.

An annual assessment of the positioning strategies of the leading 21 BI vendors finds a lack of differentiation that makes it difficult for buyers to compare products. In the BI market’s sea of sameness, Qlik is the only vendor that stands out with this clever, memorable position. Published at: https://www.eckerson.com/articles/independent-study-bi-vendor-messaging-shows-lack-of-differentiation

“Universal” semantic layer tools introduced in recent years promise to standardize business metrics across the data stack, and eliminate silos of metrics trapped in semantic layers that are limited to specific data sources or BI platforms. This post offers considerations for adopting a universal semantic layer. Published at: https://www.eckerson.com/articles/the-universal-semantic-layer-more-than-enough

This article, the third in a series, dives into the technologies that underpin modern approaches to location intelligence. It explores databases for industrial-scale geospatial applications, advanced business intelligence (BI) tools for exploratory analysis, and simple use-case specific platforms. Published at: https://www.eckerson.com/articles/location-intelligence-part-iii-enabling-technologies

In this article, Lawson Abinati lays out core principles for market positioning that apply across all industries, as well as to Business Intelligence (BI) professionals. Although many business intelligence (BI) managers see themselves as technologists first, unless they understand the soft skills of sales, marketing, and communication, they won't succeed professionally or make good on their organization's investments in BI. Published at: https://www.eckerson.com/articles/what-is-positioning-and-why-is-it-important

Gordon Wong is on a mission. A long-time business intelligence leader who has led data & analytics teams at HubSpot and FitBit, Wong believes BI teams aren’t data-driven enough. He says BI leaders need to think of themselves as small businesses owners and aggressively court and manage customers. He says too many don’t have metrics to track customer engagement and usage. In short, BI teams need to eat their own dog food and build success metrics to guide their activities.

If you are a data or analytics leader, do you know the value your team contributes to the business? Do you have KPIs for business intelligence? Can you measure the impact of data and analytics endeavors in terms the business understands and respects? Too often BI and data leaders get caught up in technical details and fail to evaluate how their technical initiatives add value to the business. This wide-ranging interview with a BI veteran will shed light on how to run a successful BI shop.

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

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.

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 technology officer of Sage Hospitality, one of the world's largest hotel operators. Although Matt is responsible for all aspects of Sage’s IT operations, he has a deep fondness for data and analytics, having served as a BI director for several companies, including PetSmart and Staples. Matt firmly believes in the power of BI tools to transform organizations.

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

Explore how data analytics leaders can balance the use of specialists and generalists.

Originally published at https://www.eckerson.com/articles/specialists-or-generalists

Just-in-time design is the practice of designing working software in small increments that support a business-defined need or story. Just-in-time design, as well as just-in-time testing, is an integral part of the agile software methodology. In fact, you can’t really do agile without just-in-time design.

To help us understand the nuances of just-in-time design, we invited Aaron Fuller, a long-time data architect and member of Eckerson Group’s consulting network. Across an 11-year career as the enterprise data architect for an insurance company, he modeled data, created technical designs for a broad range of systems, established governance and stewardship, and led the establishment of their enterprise data warehousing, business intelligence, and enterprise architecture programs. As principal consultant and owner of Superior Data Strategies since 2010, he leads a team of highly skilled data professionals who are uniquely capable of planning and executing agile data projects.

Why is Data Quality still an issue after all these years? To get an answer to the prevalent question, Wayne Eckerson and Jason Beard engage in a dynamic exchange of questions which lead us to the root cause of data quality and data governance problems. Using examples from his past projects, Jason shows the value of business process mapping and how it exposes the hidden problems which go undetected under the standard IT lens.

In his most recent role as Vice President of Process & Data Management at Wiley, a book publisher, he was responsible for master data setup and governance, process optimization, business continuity planning, and change management for new and emerging business models. Jason has led business intelligence, data governance, master data management, Process Improvement, Business Transformation, and ERP projects in a variety of industries, including Scientific and Trade publishing, Educational Technology, Consumer Goods, Banking, Investments, and Insurance.

In this episode, Daniel Graham dissects the capabilities of data lakes and compares it to data warehouses. He talks about the primary use cases of data lakes and how they are vital for big data ecosystems. He then goes on to explain the role of data warehouses which are still responsible for timely and accurate data but don't have a central role anymore. In the end, both Wayne Eckerson and Dan Graham settle on a common definition for modern data architectures.

Daniel Graham has more than 30 years in IT, consulting, research, and product marketing, with almost 30 years at leading database management companies. Dan was a Strategy Director in IBM’s Global BI Solutions division and General Manager of Teradata’s high-end server divisions. During his tenure as a product marketer, Dan has been responsible for MPP data management systems, data warehouses, and data lakes, and most recently, the Internet of Things and streaming systems.

In this episode, Wayne Eckerson asks Steve Dine about the approach needed to migrate to the Cloud and architecture required to run analytics in the Cloud. Steve Dine talks extensively about the pitfalls to avoid during Cloud migration and finishes off by saying that even though security is a big issue, most organizations will have part of their architecture in the Cloud during the next two-three years. Steve Dine is a BI and enterprise data consultant and industry thought leader who has extensive experience in designing, delivering and managing highly scalable and maintainable modern data architecture solutions.

BI teams often work extremely hard but have little to show for their effort, and they can never get ahead of a continuous backlog of requests. The business rewards their hard work by reducing their budget and staff. Even if they know what needs to be done, they have little authority to make it happen. To succeed, BI leaders need to partner with the business and deliver quick wins to turn the tide of adoption in their favor.

Originally published at https://www.eckerson.com/articles/why-bi-teams-struggle-the-tipping-point-of-success

In this Episode, Wayne Eckerson asks Charles Reeves about his organization’s Internet of Things and Big Data strategy. Reeves is senior manager of BI and analytics at Graphics Packaging International, a leader in the packaging industry with hundreds of worldwide customers. He has 25 years of professional experience in IT management including nine years in reporting, analytics, and data governance.

A classic management practice dictates that a newly-appointed leader must accomplish certain things in their first 90 days. While some of this is general knowledge, there are specifics when it comes to Data Management and Analytics If you have been recently named to head any group that has to manage or facilitate the use of data, at any level in the organization, then this audio blog post is for you.

Originally published at https://www.eckerson.com/articles/what-do-you-do-first-after-being-hired-as-a-bi-analytics-data-engineering-director

With all the hype and attention around big data and huge data platforms, there can sometimes be some data envy. There are still organizations and companies that don’t have big data: are they not poised for analytics too? Can they not get insights as well? The BI Pharaoh gives tips on how to work with your little data just like the big boys.

Originally published at https://www.eckerson.com/articles/little-data-needs-love-too

We’re at the dawn of a new era in decision making made possible by the intersection of business intelligence and artificial intelligence. Rather than replace BI, AI will make BI more pervasive. AI-infused BI tools will be easier to use, generate more useful insights, and make business users more productive. Rather than replace human decision makers, AI will free them to focus on value-added activities and make decisions with data rather than rely solely on gut instinct.

Originally published at https://www.eckerson.com/articles/the-impact-of-ai-on-analytics-machine-generated-intelligence

In this episode, Wayne Eckerson and Rich Galan discuss the obstacles to delivering timely analysis, the problems that large volumes of data create, solutions to those issues, and where BI is headed in the near future. Rich is a veteran data analytics leader with 20 years of experience in a variety of data-driven organizations.