Whitepapers
Datanami's white paper database contains reports from the leading thought-leaders and idea generators in the Datanami industry. 
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…
What makes the difference between an average enterprise and a market leader? A strong data and analytics culture, producing vital information that informs decision-making and behavior throughout the business.
But a failure of analytics and processes around data can open up Information Gaps that divide teams and silo data, leaving enterprises in the dark and struggling to catch up as their data-savvy competitors seize new opportunities and widen their lead in the market. Read more…
Whether you call it data preparation, mining, extracting, cleaning, joining, blending, or masking, it’s all data transformation. Professionals can spend hours every week working with their data, trying to join data from disparate sources, re-keying info from static reports or PDFs, or formatting data for accurate reporting. Read more…
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