Although dashboards will never disappear, they will be radically transformed by artificial intelligence. They will become more intelligent, predictive, timely, and conversational.
Before a company hires data science talent, they should understand the role and types of data scientists. Failing to differentiate between research, applied, and citizen data scientist can result in appointing the wrong people on crucial projects. To continue our previous episode's discussion, we invited Alex Vayner for a second time to get an answer to the question: What is a data scientist? Alex Vayner is a Partner and Americas Data & AI Practice Leader for PA Consulting Group, an innovati...
Explore how data analytics leaders can balance the use of specialists and generalists. Originally published at https://www.eckerson.com/articles/specialists-or-generalists
New challenges to analytics platforms have prompted SAS to create new responses. The software giant responds with automation and decision support tools.
Data science has made immense progress, but companies are still stuck with the question: how do you use data science to deliver real value to the business? They hire dozens of data scientists and invest in state-of-the-art technology, but only a few have delivered ROI and business impact. In this episode, Wayne Eckerson and Alex Vayner discuss what organizations need to do for data science success. Alex Vayner is a Partner and Americas Data & AI Practice Leader for PA Consulting Group, an in...
IoT has created a tidal wave that data savvy organizations can turn into profitable business solutions. Most IoT data comes from sensors, which are now attached to almost every device imaginable, from factory floor machines and agricultural fields to your cell phone and toothbrush. But IoT is forcing companies to rethink their data architectures to ingest, process, and analyze streaming data in real-time. To help us understand the impact of IoT on data architectures, we invited Dan Graham to our...
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 e...
Last month, I attended Domo’s annual user conference for the first time. I came a skeptic, but left a believer. Domo has invested large sums of money to create a comprehensive data and analytics platform that scales to run small and medium-size businesses, and possibly large ones. Most importantly, it has a cadre of highly satisfied brand-name customers who want to extend the platform to support all business users and their analytic applications. Originally published at: https://www.eckerson.com...
Processing continuous data streams is becoming increasingly important. However, traditional analytics architectures were often not built for real-time scenarios. This article will illustrate challenges and discuss how streaming-first approaches can change the way we think about analytics architectures. Originally published at: https://www.eckerson.com/articles/streams-everywhere-towards-streaming-first-architectures
This second article in a series on modern data architectures. It focuses on what drives customers to want a modern data architecture (i.e., fear and opportunity) in the first place. It then lists ten requirements that customers desire for a modern data architecture, ranging from “cloud-first” and “streaming-first” to “best of breed” and “predictable pricing”. Originally published at: https://www.eckerson.com/articles/ten-things-companies-want-from-a-modern-data-architecture
Data virtualization has been around for decades and has always been controversial. In the 1990s, it was called virtual data warehousing or VDW-- or as some skeptics liked to say, "voodoo and witchcraft”. It’s also been known as query federation and more recently, data services. The idea is that business users don't need to know the location of the data; they merely need to log into the data service and all data appears as if it’s local to their server, modeled in a fashion that makes sense to th...
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 Managem...
Being a change agent is hard. It's tough to inspire people and get them motivated to work on a shared vision. To understand the mechanics of digitalization and tactics required to implement them, Wayne Eckerson invited Andrea Ballinger so that she could share her hard-won lessons from her illustrious career as a technology leader. Andrea is currently leading a transformation program at LSU, revamping the university’s information technology resources across multiple campuses. Prior to that, she s...
The road to AI adoption is far more complex than one can imagine. Building data science models and testing them is only one piece of the puzzle. To understand the roadblocks and best practices, Wayne Eckerson invited Nir Kaldero in our latest episode to learn why organizations need to start paying more attention to people, culture and processes to make data science projects a success and how democratization skills pays off in the long run. Nir Kaldero is the Head of Data Science, Vice President ...
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 year...
Recent technology developments are driving urgency to modernize data management. What do you do about architecture, modeling, quality, and governance to keep up with big data, cloud, self-service, and other trends in data and technology? Examining some best practices can spark ideas of where to begin. Originally published at https://www.eckerson.com/articles/stepping-up-to-modern-data-management
Data catalogs have become the centerpiece of modern data management. They are the means to connect self-service analysts with the right data, the “go to” technology for data curation, and the new gold standard for metadata management. With many data catalog tools available, choosing the right data catalog is an important decision.
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 extensiv...
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-s...
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 data analyst workbench will inevitably integrate data catalog, data preparation, and data analysis functionality. Data analysts don’t want to jump from tool to tool when executing a workflow that is both linear and iterative. Data analysts with this kind of workbench will be more productive and foster higher levels of reuse and data literacy. Originally published at https://www.eckerson.com/articles/self-service-triumvirate-the-new-data-analyst-workbench
In this episode, Wayne Eckerson and Shakeeb Ahkter dive into DataOps. They discuss what DataOps is, the goals and principles of DataOps, and reasons to adopt a DataOps strategy. Shakeeb also reveals the benefits gained from DataOps and what tools he uses. He is the Director of Enterprise Data Warehouse at Northwestern Medicine and is responsible for direction and oversight of data management, data engineering, and analytics.
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...
In this episode, Wayne Eckerson and Rich Fox discuss what differentiates data science from analytics, why and how data science addresses business needs, why balance scorecards are relevant, and why Excel is a problem. Throughout the podcast, Fox shares many real-life examples and personal experiences. Fox is vice president of Data Science and Analytics at Apex Parks Group, one of the largest entertainment center companies in the United States, which operates amusement parks, water parks, and fam...
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 h...
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.
Data analysts who sit in each business function (i.e., sales, marketing, finance) are critical to the success of a self-service analytics strategy. The problem is that most data analysts don’t receive the training and support they need to be proficient with self-service data and analytics tools. The easiest way to improve the skills and satisfaction of most data analysts is simple: bring them together into a power user network. Originally published at https://www.eckerson.com/articles/power-user...
In this episode, Wayne Eckerson and Steve Dine discuss modernizing data architectures. They cover the definition of a modern data architecture, telltale signs you need to modernize, best practices to modernize, and much more. Dine is the President of Datasource Consulting, an EXL company. He has extensive experience designing, delivering, and managing successful, highly scalable and maintainable modern data architecture solutions.
Data pipelines become chaotic with pressures of agile, democratization, self-service, and organizational “pockets” of analytics. From enterprise BI to self-service analysis, data pipeline management should ensure analysis results are traceable, reproducible, and of production strength. Robust data pipelines rely on eight critical components. Originally published at https://www.eckerson.com/articles/the-complexities-of-modern-data-pipelines
