Typically when we think of big data, we think of large corporations that have the tools and resources to make sense of all their data. However, mid-market companies are beginning to explore how to leverage big data effectively, too. Like larger corporations, mid-market companies can experience many benefits when they have a proper big data strategy in place. By following larger corporations’ lead, mid-market companies can leverage their existing big data to increase revenue and improve customer relationships.
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Below are three tips for mid-market companies seeking to implement a productive big data strategy:
1. Understand What You Want to Get Out of Your Big Data
In order to successfully take advantage of all the benefits big data has to offer, companies must first determine how they will use big data in a competitive landscape. In other words, what big data benefits will help them stay ahead of their competitors? E-retailers may want to know shopping trends in real-time, while manufacturers may be more interested in material shortages and quality control measures. For instance manufacturers should take advantage of big data to analyze the availability of raw material supplies, coupled with their production line forecasting in order to accurately anticipate demand . Once companies can understand and recognize their business needs, they’ll know how to best use their data.
2. Incorporate Business Intelligence Tools
Business intelligence solutions allow companies to turn their raw data into immediately meaningful and useful information for business analysis purposes. If companies try to skip this step, they won’t fully understand all the information big data can provide. With the right tools, companies can easily integrate all of their corporate data assets into a central repository with meaningful dashboards that highlight key performance indicators (KPIs) for their business. Before companies select a business intelligence tool, however, it is important to make sure the ERP data is as clean as possible. In addition, companies should be sure to examine other criteria such reporting capabilities and easy-to-use dashboards.
3. Leverage Analytics
Big data requires extensive processing and analyzing, so handling this manually is not an accurate or efficient option. Big data analytics software can help companies accurately predict the future by analyzing current as well as past trends. To do this, companies should have databases in addition to SQL, such as in-memory databases. Many databases from the big players such as IBM and Microsoft have in-memory capabilities built in, which gives companies the performance needed for real-time processing. These built-in capabilities help mid-market companies take advantage of big data analytics without the additional skills required for open source or Hadoop databases.
Still hesitant about exploring big data? Don’t be. Mid-market companies just need to optimize requests for specific trends versus general trends that produce too much data to act upon. While mid-market companies may not have the same resources or budget as larger organizations, they can learn from larger companies’ best practices and leverage examples of their big data successes and failures to their advantage.
Kevin Beasley is CIO at VAI.