In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes. Information is often redundant and analyzing data requires combining across multiple formats, including written documents, streamed data feeds, audio and video. This makes gathering information for decision making a challenge.

The COVID-19 pandemic and the resulting economic uncertainty forced businesses to rethink how they approach growth. This especially rang true in the financial services industry, where financial trends have the most direct impact. Curiosity, collaboration, and adaptability all became key to surviving this new climate.

The Defense Information Systems Agency (DISA) launched an ambitious program with a name as intimidating as the effort to re-imagine the security architecture of the Department of Defense (DoD). Thunderdome is DISA’s zero trust network access and application security architecture.

In large organizations, Confluent Cloud is often simultaneously accessed by many different users along with business-critical applications, potentially across different lines of business. With so many individual pieces working together, the risk of an individual outage, error, or incident affecting other services increases. An incident could be constituted by a user clicking a wrong button, an application’s misconfiguration, or just a bug—you name it.

Regression testing is an important practice in software development. It tests to ensure your application remains stable and reliable even as changes and updates are introduced. Each new change introduces a risk of breaking existing functionalities, potentially causing shipping delays or launch postponements. Evaluating your application against a full suite of tests helps find and fix unexpected software bugs or errors.

Medical affairs has grown to become a core pillar of the pharmaceutical industry, linking the work of research and development and commercial operations. However, for leaders in the industry, navigating the process and data complexities and communication silos involved can prove challenging.

Data is one of the most valuable commodities an organization has. Every company stores and manages a substantial amount of information. But how do you gain revenue from it? Here, we discuss three ways you can monetize data with an embedded analytics investment.

You’ve heard of throwing ideas at a wall until something sticks–as a product manager, you may find you’re doing the same with application features. For application teams, creating sticky applications that customers can rely on and continue using for years to come is key to maximizing revenue. Elements like intuitive interfaces, personalized experiences, seamless integrations, and valuable core functionalities all contribute to this stickiness.

As I have explored in this “Sliding Doors” blog series, identifying the right door to create value with data can prove quite challenging - and once that door is opened, the journey ahead can seem daunting. But what if there was a way to make that journey a bit easier? Maybe it’s time to get back to basics… Who needs to hear this?

Data governance covers processes, roles, policies, standards, and metrics that help an organization achieve its goals by ensuring the effective and efficient use of information. It sets up the processes and responsibilities necessary to maintain the data’s quality and security across the business. Data governance manages the formal data assets of an organization.