How to Use Big Data for Midsized Companies

One of the biggest misconceptions about big data is that it’s only viable for massive enterprises, which it is not and this error in thinking creates a barrier of sorts for midsize and smaller companies. Most of this misunderstanding stems from a lack of comprehension as to how big data is treated and why it is a necessary component for companies looking to grow.

To help flesh out what big data is, when data scientists discuss big data, they are describing an enormous volume of data that is moving at a high velocity from a variety of sources in hard-to-read formats.1 This is why big data requires algorithms and processes that surpass the capabilities of traditional software, like Microsoft Excel.

Growing Importance of Big Data

Companies that invest in big data get a clearer understanding of the customer’s wants and needs, bringing more personalized solutions at a faster rate than before. The amount of data that businesses must navigate through has been growing, and will continue to grow at an exponential rate, with 2.5 quintillion bytes of data generated in 2013 alone.2As more companies continue to change their industry landscape by adopting cloud computing and virtualization, this number doesn’t appear to be slowing down.

Big data has been the driving force behind many success stories, such as Uber and their surge pricing model. Uber uses big data to shift up or down its pricing based on predictions made on the demand for rides, around the world. Not only does this offer riders the best price for the ride, it also keeps the pool of drivers under control to make their most profit.


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Starting Your Big Data Initiative

Build Qualified Infrastructures

Rebecca Shockley, Global Research Leader for Business Analytics at the IBM Institute for Business Value, shared her insights in a 2012 report on what midsize companies need before they can reap the performance benefits of big data. Her report stressed that midsize companies must first invest in their data infrastructure.3 The infrastructure must be able to handle massive volumes of data, as well as be scalable to meet future growth in system demands.

Many companies eager to adopt big data go straight into analytics without fully understanding the complexity and volume of data coming in. It is recommended for IT teams to stay involved throughout the entire big data adoption process to insure that systems will be able to support the process.4

The Need for High-Capacity Data Warehouses

The next step is to have a storing location large enough to house the big data. For many data intelligence processes, this involves adding more processing power to warehouses to handle processing the larger volumes of data coming in.5 As more information is added to data repositories overtime, the processing power will need continual optimization to manage the workload.

Powerful Analytical Tools

After a big data storage system has been settled on, then companies can focus on the extraction of information from the big data. Midsize companies have a multitude of tools available for big data analytics. The focus here is to obtain tools that utilize heavy algorithms, specifically tools that speed up the analytical process, that are designed to do most of the processing for your IT team.6

Most midsized companies don’t have the budget for an exceptionally large IT staff or sophisticated resources needed for big data. Having the proper analytical tools in place will narrow the gap between your current resources and the workload capabilities needed to analyze big data.7 While most companies can get away with using traditional software, this isn’t practical at scale because it leads to sluggish performance with many processing barriers.

Big Data Leads to Opportunities

Integrating the use of big data into your business process will reveal new business opportunities and lead to answer to the hidden problems within your service or product. Many smaller companies have created a market share for themselves by extending the reach of their abilities through big data. They were able to see beyond the initial point of sale and directly into what the customer needs as an individual.

Tiempo Development offers big data analytics services to help your company collect data for actionable insights, as well as design and build data warehouses and infrastructure. For more information on how Tiempo Development can help your company start its big data initiatives, contact us here !

  1. Big Data: What is it & why it matter. SAS.
  2. Adam K. “5 Small Ways to Use Big Data to Majorly Improve Business”. Entrepreneur.
  3. Big data: Why it matters to the midmarket”. IBM.
  4. Joanna S. “Big Data and the Midmarket: Identifying and Overcoming the Top Challenges”. TDWI. 
  5. Big data: Why it matters to the midmarket”. IBM. 
  6. Ibid.
  7. Ibid.
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