The Building Blocks of Data Science

Join Google Cloud, SpringML, and Carahsoft for a webinar as we explore a framework for combating fraud, waste, and abuse. It’s not enough to chase down fraud after it happens — our solution helps you proactively identify fraud, waste, and abuse before it infiltrates your system and doesn’t penalize legitimate claims.

Today’s most successful organisations are utilising data to drive accelerated growth. They are each on a journey towards greater data maturity, increasing the value of their data and deepening their insights as they go. However, the rapid growth of analytic solutions has not successfully transformed every business into a data-driven powerhouse – yet. So how can you ensure the route you take to AI maturity is a successful one? As with any endeavor, your company will face obstacles as you strive to transform into a data-driven organisation. To succeed, it’s important to evaluate where you are today, the challenges that lie ahead, and what exactly “ahead” means for you and your team.

The entire business community — not just your data experts — uses data. How do you build a “village” of stakeholders throughout the organization to execute a data governance program? And how can a data catalog accelerate adoption?

With data coming from so many different sources nowadays (both old and new, both internal and external), it is inevitable that data will arrive in many different structures, schema, and formats, with other variables for latency, concurrency, and requirements for storage and processing. When data types are extremely diverse and combined, we now call it “hybrid data.” This usually drives users to deploy many types of databases and different platforms to capture, store, process, and analyze the data, which in turn results in hybrid data management architectures.