Think about the monotonous task of extracting data from sources like spreadsheets and emails and typing it into various systems. Repetitive tasks and manual workflows lurking inside business processes slow down teams, introduce human error, and erode employee engagement. Slow, ineffective processes can also kill an organization’s time to market and customer satisfaction.

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?

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.

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.

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.

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.

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.

The payments industry is evolving rapidly, fueled by technological advancements, changing consumer behaviors, and a growing appetite for real-time transactions. As this transformation unfolds, new standards have been introduced to ensure the payments ecosystem's safety, security, and efficiency.

For data engineers, the Generative AI (Gen AI) era is a transformative shift in how we approach data architecture and analytics. Professionals at the forefront of this shift will be gathering in San Francisco, at the Data+AI Summit June 10-13. Attendees will be exploring tools that integrate with Databricks Intelligent Data Platform that decrease data management costs and improve data's impact on business outcomes.