Five Ways to Accelerate Your Data Analytics Journey

You’ve been collecting great data, yet how much of it falls on the virtual floor? Most organizations can capture data from the Internet of Things, corporate systems, social media and other sources, but haven’t quite mastered turning that data into business value. This is a point underscored in a new report from Prowess Consulting that is focused on accelerating the data analytics journey.

“Your organization is awash in data, arriving from different sources, in different formats, and destined for different uses,” the report notes. “And most data is never analyzed or used.”

On the upside, Prowess notes that organizations do want to take full advantage of all their data by putting sophisticated analytics and artificial intelligence to work to extract valuable business insights from all those bits and bytes. But how do you get there?

A good first step is to start with this report, sponsored by Dell EMC and Intel®. In the report, Prowess offers straightforward guidance on five overarching steps your organization can take to gain more value from all that data piling up on your enterprise and cloud servers.

Here’s a quick version of the story.

1. Take a holistic view of your data lifecycle.

Step back and look at your whole data lifecycle, from creation to archiving. Think in terms of optimizing across the continuum, beginning at the edge, where data is created, and reaching all the way to the end, to the archival stage.

2. Focus on optimizing data early in its lifecycle.

Take control of data starting at its point of origin, from remote cameras, the Internet of Things and more. As much as possible, compress it, shape it and process it before bringing it into your system. This front-end work can reduce the amount of data you need to transmit, store, protect and archive.

3. Rethink staging.

Think differently about server memory and storage, because Intel® Optane™ technology may be able to bridge those two worlds. For example, you can now put large amounts of non-volatile data on the memory bus right by the processor. Rather than thinking about storing data, think about pre-positioning it to get it in the right place and the right format and on the right media.

4. Create a scalable, flexible infrastructure for analytics and AI.

Don’t wed yourself to a particular framework or algorithm. And don’t get stuck with hardware that can do only one thing. Break down the infrastructure and analytics silos. Build cloud-like, multipurpose, HPC infrastructure that can run AI workloads alongside other workloads.

5. Prepare for AI and ML everywhere.

Think of AI as a valuable tool for optimizing data across your business. Use intelligent edge devices to preprocess data using pattern matching. Use AI to identify suspicious traffic in your network. Don’t think of AI as a destination for your data at the end of its lifecycle. Think about AI being everywhere.

Moving forward

Dell EMC and Intel offers solutions for each step in the process of accelerating your data analytics journey. These offerings extend from intelligent edge devices to PowerEdge servers to new Dell EMC Ready Solutions for HPC and AI that provide all the hardware, software and services you need to get a deep learning solution up and running quickly. The Prowess report highlights many of these offerings, and explains how you can put them to use to accelerate your data analytics journey.

To learn more

About the Author: Janet Morss

Janet Morss previously worked at Dell Technologies, specializing in  machine learning (ML) and high performance computing (HPC) product marketing.