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Why Data Analysts End Up Playing Data Detective

Many data analysts are getting a raw deal. For all the optimism around cloud-based systems promising to make Data Management easier, analysts often wind up playing detective ­– battling through huge information stores on the hunt for useful data, instead of running analysis. For companies, the disillusionment driven by lumbering valuable (and rare) specialists with manual processing […]

Real-Time Analytics: Examples and Benefits

Technology behemoths like Netflix, Uber, and Meta set the standard for how application users experience data. Users expect data to be integrated into the application, making it easier to find relevant content, track deliveries, provide a spam-free internet experience, and make quick, informed operational decisions. Up until this point, the speed and scale of real-time analytics […]

Augmented Analytics Tools Can Enable Data Democratization

What is business intelligence democratization? Put simply, BI democratization is the open access to business intelligence and augmented analytics tools to enable analysis and understanding of the data within the enterprise systems. The “democratization”  component relates to the “who.” Who gets access to the data? The simple answer is: everyone.  In an environment where intelligence and […]

Are Data Warehouses Still Relevant?

Over the past few years, enterprise data architectures have evolved significantly to accommodate the changing data requirements of modern businesses. The emergence of advanced data storage technologies, such as cloud computing, data hubs, and data lakes, makes us question the role of traditional data warehouses in modern data architecture.  Data warehouses were first introduced in the […]

What’s a Semantic Layer Worth?

There’s been a lot of talk about semantic layers lately. I’ve seen dozens of companies using a semantic layer to drive self-service analytics at scale. But even with all these success stories, I still get this question: “Is a semantic layer worth the effort?” In other words, is the juice worth the squeeze?  So, how […]

Developing Agile Data Warehouse Architecture Using Automation

In the past, designing and developing a robust data warehouse that satisfied the need for timely and effective business intelligence (BI) was an overwhelmingly difficult task, as it required significant time, capital, and risk. However, the advent of agile data warehouse architecture has truly transformed how enterprises build their data architecture and enable business intelligence. In essence, agile […]