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

Big Data & Analytics Maturity Survey Report 2020

Source: AtScale
Release Date: May 18, 2020

Learn where Data, Analytics, and IT leaders are with their 2020 enterprise cloud strategy, their data and analytics priorities, and what their biggest challenges are. You’ll get key insights on their priorities around data virtualization, data governance, and data security across their on-premises and multi-cloud environments. Read more…

10 Rules for Managing Kafka

Source: Instaclustr
Release Date: May 15, 2020

Kafka is not difficult to use, but it is tricky to optimize. It has evolved from essentially a message queue to a versatile streaming platform. Read the 10 golden rules of managing Kafka that will help you perfect your Kafka system and stay ahead of the curve. Read more…

Six Success Factors for Getting Started with Machine Learning Across Your Enterprise

Source: H2O
Release Date: May 7, 2020

There is a wide range of ML use cases that can help organizations grow. However, the technology is still primarily in the early mainstream adoption stage. At TDWI, they see that many organizations get stuck when they start to make use of the technology, which can prevent it from being used in other parts of (or even across) the organization. Read more…

Data Virtualization: Your Blueprint for Choosing a Solution

Source: AtScale
Release Date: Apr 8, 2020

This buyer’s guide lays out key considerations for organizations looking to apply data virtualization to their analytics use cases. Along with key features and capabilities, you’ll learn about the difference between data virtualization and query federation, drill down on caching techniques and get a detailed feature ranking worksheet for evaluating vendors in the space. Read more…

Best Practices for Data Visualizations

Source: GoodData
Release Date: Apr 7, 2020

It’s not surprising that with the right data visualizations, you can tell a compelling data story and help your audience figure out what actions they should take next. To make this easier for everyone, GoodData asked data analytics experts for their insights and best practices regarding data visualizations, which are compiled into this ebook. Read more…

The Role of Middleware in Optimizing Vector Processing

Source: NEC
Release Date: Apr 1, 2020

Data generated globally is growing at a massive rate that will increase exponentially as the predicted billions of IoT devices add their weight to the stack, reaching what analysts at IDC believe will be 79 trillion GBytes in 2025. Read more…

Modernize Your Data Warehouse

Source: Matillion
Release Date: Mar 26, 2020

You have BIG Data. However, growing varieties, volumes, and velocities of data can strain your database and existing BI processes.

Trying to cope with these increases will unearth platform limitations that are not easily overcome and can be expensive to work around because legacy on-prem systems were never designed to handle the pressures of modern data demands. Read more…

Overcoming Obstacles to Machine Learning Adoption

Source: H2O
Release Date: Mar 25, 2020

After many fits and starts, the era of enterprise machine learning has finally arrived. According to 451 Research’s Voice of the Enterprise, AI and Machine Learning survey, 20% of enterprises have already deployed the technology and a further 33% plan to do so within one year. Read more…

12 Steps to a Successful Analytics Organization

Source: Tamr
Release Date: Feb 13, 2020

Analytics and data are about people and empowering them. Analytics start with questions, from real people, at all levels of an organization. What if people in your organization could easily and accurately answer the 100, 200, or even 500 questions that would create significant value by using all the data in your organization at any time? Read more…

Native Parallel Graphs; The Next Generation of Graph Database for Real-Time Deep Link Analytics

Source: TigerGraph
Release Date: Jan 16, 2020

TigerGraph’s eBook “Native Parallel Graphs: The Next Generation of Graph Database for Real-Time Deep Link Analytics,” discusses what developers need to learn in order to leverage the power of graph analytics for the most complex business problems. Read more…

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