Whitepapers
Datanami's white paper database contains reports from the leading thought-leaders and idea generators in the Datanami industry. 
Discover the four key capabilities you should look for in an AI platform.
We all know the potential of AI is massive. It can transform everyday business data into increased revenue, cost savings, and new business opportunities. Read more…
But as cloud data workloads, regulations, and ecosystems evolve, managing data security at scale has overwhelmed data engineering teams. What can data platform owners do to return to simplicity?
In this eBook, you’ll learn: Read more…
Data-driven decision-making and the ability to drive meaningful insights from increasing volumes of data is no longer just a competitive advantage: it’s a requirement for business leaders.
However, as the volume and complexity of data grows, data teams still struggle to manage data migration and maintenance, causing new and growing information gaps as well as burnout across the teams. Read more…
While compliance requirements increase the number of strict limitations placed on data, the need for quick and easy access remains integral to the productive use of said data.
With data-driven businesses trapped in the middle, can this problem be solved while still meeting each side’s needs? Read more…
Organizations have been investing in data science, analytics, and BI resources and tools for years to reap the benefits of data-driven decision-making. But as sensitive data use has become more common – and even expected – and data rules and regulations expand and evolve, new challenges have emerged that threaten to hinder data pipelines and results. Read more…
MongoDB is widely used as an operational database, but there is typically a need for real-time analytics on MongoDB data for data applications and operational analytics. In this ebook, we discuss some of the challenges involved with running complex queries over large-scale data in MongoDB including performance impact on transactional workloads, lack of support for SQL and joins, performance Engineering effort for analytics. Read more…
PostgreSQL is a powerful and extensible technology that can solve a lot of problems in all different kinds of environments. Use cases for PostgreSQL are growing exponentially over time. That is, the number of applications that PostgreSQL can target is becoming greater as time goes by, and (more importantly) the number of applications that it can’t target is going down. Read more…
Changes in data warehousing result in changes and developments in the supporting processes, applications, and technologies. As such the origin, growth, and decline of ETL can be mapped directly against data warehousing innovations. Read more…
In the second annual DataAware Pulse Survey, it was more clear than ever that data teams are facing a new and painful scaling challenge: scaling team productivity. The growing requirements businesses are placing on data teams are quickly outpacing team growth, and data engineers, analysts, scientists, and more are now struggling to keep pace. Read more…
We experience real-time analytics everyday. The content displayed in the Instagram newsfeed, the personalized recommendations on Amazon, the promotional offers from Uber Eats are all examples of real-time analytics.
Real-time analytics encourages consumers to take desired actions from reading more content, to adding items to our cart to using takeout and delivery services for more of our meals. Read more…
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