KDnuggets Home » News » 2015 » Jul » Opinions, Interviews, Reports » Big Data Best-Practice Checklist for Small and Medium Enterprises ( 15:n25 )

Big Data Best-Practice Checklist for Small and Medium Enterprises


As more and more companies getting into the competition, it is important for the SMEs to get Big Data right from the start. Learn, how you can make most of the big data analytics.



By Stuart Wells, FICO Chief Technology Officer

Expanding business use of Big Data analytics is increasing pressure on small and medium enterprises (SMEs) to become more competitive in this area, whether by developing this function or enhancing ongoing efforts. SMEs, with their traditionally smaller budgets and margin of error, need to get Big Data right from the start.

big-data-vendors

In a recent survey (page 2), 61% of respondents said improving the quality of decision making was their top priority with their Big Data investments (and 52% cited speeding up this process). To develop or improve their Big Data analytics, SMEs should consider the following to maximize business value before pushing the button on the required investment.

  1. Start with the problem. Exploring huge amounts of data with analytic tools can be lots of fun and offer lots of insights. However, it can be a waste of time and resources if the results do not translate into something that solves real-world business problems, such as queue management at large sporting events like Wimbledon.
  2. Keep up-to-date with the latest tools. The latest cloud-based solutions offer SMEs access to high-end tools at a much lower cost. These Big Data tools and infrastructure are making it easier to apply machine learning techniques to explore huge datasets that to give even the smallest companies big business insights.
  3. Cut through the noise. Given the enormous volume of data, useful information must be separated from a lot of “noise” with high-impact business analytics. You need to be able to determine whether data simply correlates or whether a true causation exists; the latter is much more useful.
  4. Expand access to Big Data. Giving all employees access to data can really ensure that you are getting the most out of your insights. Whether the sales team are using data to retain customers or the HR department simply wants to know how much coffee the team is drinking, Big Data is useful to all aspects of your business.
  5. Use the insight of business experts. To identify projects that are both promising and practical, work with business experts to understand their challenges and opportunities. It is also vital to understand the types of problems the various types of Big Data and analytic techniques can solve.
  6. Analyse data in real-time. Innovations in Big Data processing and analytics are transforming how businesses get value from their data. We’re seeing a shift from descriptive reports and dashboards to systems that continuously analyse incoming data to produce predictions that are actionable in real-time.
  7. Visualize it. The whole point of Big Data analytics is to give business experts new insights they can quickly turn into decision strategies that will ultimately improve customer impact. For instance, visual tools that build decision trees allow business experts to quickly segment customer populations using any mix of policies and data-driven insights.
  8. Balance Big Data with human insight. The right balance of Big Data techniques with human expertise not only lifts business performance, it also improves the ability of companies to learn at a fast pace from data-driven experiments.

Creating Big Data analytics no longer requires making a huge investment in expensive infrastructure and specialised skills. By leveraging cloud services, companies can let someone else securely handle the underlying systems and services, paying just for the capacity and services they need. There’s no need to reinvent the wheel—just take advantage of its momentum.

Bio: Dr. Stuart C. Wells, is an Executive Vice President, Chief Product and Technology Officer of FICO.

Related: