By now, many companies have decided that big data is not just a buzzword, but a new fact of business life -- one that requires having strategies in place for managing large volumes of both structured and unstructured data. And with the reality of big data comes the challenge of analyzing it in a way that brings real business value. Business and IT leaders who started by addressing big data management issues are now looking to use big data analytics to identify trends, detect patterns and glean other valuable findings from the sea of information available to them.
It can be tempting to just go out and buy big data analytics software, thinking it will be the answer to your company's business needs. But big data analytics technologies on their own aren't sufficient to handle the task. Well-planned analytical processes and people with the talent and skills needed to leverage the technologies are essential to carry out an effective big data analytics initiative. Buying additional tools beyond an organization's existing business intelligence and analytics applications may not even be necessary depending on a project's particular business goals.
This Essential Guide consists of articles and videos that offer tips and practical advice on implementing successful big data analytics projects. Use the information resources collected here to learn about big data analytics best practices from experienced users and industry analysts -- from identifying business goals to selecting the best big data analytics tools for your organization's needs.
1. News and perspectives on big data analytics technologies
Big data has been getting lots of attention for what it can possibly reveal about customers, market trends, marketing programs, equipment performance and other business elements. For many IT decision makers, big data analytics tools and technologies are now a top priority. These stories highlight trends and perspectives in the rapidly expanding world of big data analytics.
2. Best practices for implementing big data analytics projects
The stories in this section offer a closer look at what makes big data analytics work -- and what doesn't. Experts share best-practices advice for managing successful big data analytics programs, with tips for identifying business goals, selecting software, using existing resources and avoiding potential mistakes.
3. Big data analytics videos
Consultants and experienced users discuss big data analytics technologies and trends in the following videos. Speakers include Colin White, president and founder of BI Research; William McKnight, president of McKnight Consulting Group; and Wayne Eckerson, director of TechTarget's BI Leadership Research unit.
Industry analyst Colin White is tired of all the talk about the three V's of "big data." He instead wants to focus on the use cases -- the analytics -- of big data.
In a video Q&A, Timothy Leonard of U.S. Xpress explains how the trucking company uses big data analytics, real-time BI software and mobile BI apps in unison to make important business decisions.
In a video interview, business intelligence analyst Wayne Eckerson offers tips on using big data analytics software and related big data technology. He also gives his view of what big data really is.
Is there real value to be gained by analyzing "big data"? And what challenges does big data present to organizations? Consultant Jill Dyche answers those questions and more in a video interview.
Successful analytics managers mix business blue and IT red skills, TechTarget's Wayne Eckerson says in discussing his new book on analytical leaders.
4. Important terms related to big data analytics
Read the definitions below to learn more about commonly used terms related to big data and the distinctions among them.
5. Big data analytics quiz
Take this brief quiz to test what you've learned about big data analytics best practices.