Today organizations are looking for better solutions to guarantee that their data and information are kept safe and structured. Using a data lake contributes to the creation of a centralized infrastructure for location management and enables any firm to manage, store, analyze, and efficiently categorize its data. Organizations find it extremely difficult to deal with data because the information is kept in silos and in multiple formats.

You’ve likely been hearing different versions of the same idea now for a while. Enterprises in every industry are investing in technology and strategies to drive more value from all their data across their entire organization.

With Fivetran on Azure, enterprise customers can now implement fully automated, managed, no-code data pipelines for reliable and secure data delivery.

Switching to a modern ERP software system affords many benefits, including increased efficiency, improved accuracy, and better control over your company’s finances. It is also an excellent opportunity to revisit many of the business processes that sit outside of your core ERP system. As you set out to improve your financial and operational procedures, you have an opportunity to rethink the way you perform tax planning, transfer pricing, budgeting, reporting, and analytics.

In many organizations, transfer pricing adjustments are like a lot of other last-minute activities. They seem to be ignored throughout most of the annual cycle. Then, they suddenly take on a great importance at year-end. That leaves the tax team scrambling to address an entire year’s worth of transactions. It also leads to interdepartmental friction in many cases. If transfer pricing is changed retroactively for the entire year, that can have far-reaching implications.

Data plays a vital role in the growth of an organization. Companies spend large amounts of money on building data and big data infrastructures such as data vaults, data marts, data lakes, and data warehouses. These infrastructures are populated via multiple data sources using robust ETL pipelines that function throughout the day. A data infrastructure must operate 24/7 to provide real-time analysis and data-driven business insights.

A recent VentureBeat article , “4 AI trends: It’s all about scale in 2022 (so far),” highlighted the importance of scalability. I recommend you read the entire piece, but to me the key takeaway – AI at scale isn’t magic, it’s data – is reminiscent of the 1992 presidential election, when political consultant James Carville succinctly summarized the key to winning – “it’s the economy”.

Self service analytics (also called self-service business intelligence, or self-service BI) is a term commonly used among analytics vendors and organizations adopting BI, often in the context of being the next big thing in driving more people to use data to find insights. But what is self service analytics? How does self service analytics work? And why does self service analytics matter?

With the Apache Spark 3.1 release in early 2021, the Spark on Kubernetes project has been production-ready for a few years. Spark on Kubernetes has become the new standard for deploying Spark. In the Iguazio MLOps platform, we built the Spark Operator into the platform to make the deployment of Spark Operator much simpler.

Transactional databases are essential to many apps and software. Learn more about them and their benefits with Fivetran.