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Whitepapers Datanami's white paper database contains reports from the leading thought-leaders and idea generators in the Datanami industry.

10 Critical Factors for Cloud Analytics Success

Source: Informatica
Release Date: Jul 28, 2022

Guide to Achieving Faster Time to Value and ROI with Cloud Data Management

Organizations of all types are turning to intelligent, automated cloud-native data management to deliver cloud analytics that accelerates insights and drive innovation. Read more…

SQL to NoSQL: Architecture Differences and Considerations for Migration

Source: Scylla
Release Date: May 26, 2022

When and how to migrate data from SQL to NoSQL are matters of much debate. It can certainly be a daunting task, but when your SQL systems hit architectural limits or your cloud provider expenses skyrocket, it’s probably time to consider a move. Read more…

ebook: Four Must-Haves to Put AI into Practice

Source: Virtualitics
Release Date: May 19, 2022

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…

The Data Platform Owner’s Guide to Automated Data Access

Source: Immuta
Release Date: Apr 14, 2022

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…

The Data Divide: Top Challenges Facing Enterprise Data Teams

Source: Matillion
Release Date: Mar 10, 2022

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…

Automated Data Goverance 101

Source: Immuta
Release Date: Jan 13, 2022

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…

REPORT: 2022 State of Data Engineering Survey Emerging Challenges with Data Security & Quality

Source: Immuta
Release Date: Dec 9, 2021

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…

The Ultimate Guide to Real-Time Analytics on MongoDB

Source: Rockset
Release Date: Dec 2, 2021

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…

10 Rules for Managing PostgreSQL

Source: Instaclustr
Release Date: Nov 11, 2021

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…

From ETL to ELT: The Next Generation of Data Integration Success

Source: Matillion
Release Date: Nov 11, 2021

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…