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Enterprise data analytics strategy: A guide for CIOs

Last updated:August 2017

Editor's note

As enterprises seek to take advantage of ever-larger stores and sources of information, data analytics continues to take on greater importance. Modern CIOs are tasked with determining how best to capitalize on an organization's data to improve decision-making, fine-tune marketing programs, respond to changes in customer demand and seize new business opportunities.

But before technology managers can put big data to strategic use, they must first make some tactical decisions around IT infrastructure. One decision involves how big data is stored: Hadoop clusters versus traditional network-attached storage and storage-area network installations, for instance. The process of collecting, processing and analyzing large data sets also calls for a lot of processing power. Enter framework offerings like Hadoop's Apache Spark. NoSQL databases, in-memory analytics tools, distributed computing systems and converged infrastructure appliances rank among the other considerations when building a technical architecture to support a data analytics strategy.

In this CIO Essential Guide, we'll explore the potential benefits of enterprise data analytics and the technologies that enable this capability. Read on to learn big data basics and strategic guidelines, get tips on architecting the right data infrastructure, understand the advantages and complexities of Hadoop, discover real-world analytics success stories, and peer into the future of data analytics strategy.

1Get acquainted with the processing powerhouse

You can't talk about data analytics without also talking about Hadoop; it's a crucial processing technology that has changed the analytics game and become an integral part of IT ecosystems. In this section, get acquainted with the evolution of Hadoop and ponder next steps.

2Data: The new king of business strategy

In these videos, watch how IT experts are using technologies like data lakes to get the most out of big data and hear from a rising big data startup that's using analytics to change the travel business.

3Make note of these data analytics approaches

As with any area of IT, the strategic considerations involved in enterprise data analytics are abundant and, often, complicated to address. What technology or approach is best for your organization? What are some of the common data science mistakes to avoid? Should IT leaders build or buy big data architecture? This section includes tactical considerations and advice to help you navigate the testy waters of data analytics.

4How the right infrastructure can make or break your big data projects

Of course, any good data analytics strategy needs a solid foundation to build upon. IT professionals are consistently challenged with new choices on hardware, storage and other aspects of data center infrastructure. In this section, explore these choices and get tips on how to overcome infrastructure hurdles.

5Learn how organizations are using analytics to their advantage

How are other IT leaders harnessing the power of data analytics? In this section, see enterprise data analytics strategies in action and find the approach that best fits your organization's IT and business goals.

6Data analytics terminology

7Pondering the future of data analytics

How will enterprise data analytics technologies impact your organization's big-picture business models going forward? Stay attuned to the up-and-coming analytics trends and practices in this section.