Big Data is an important resource for any business, no matter what size – whether it’s a startup business or a traditional multinational. Companies are realizing that having as much information as possible can provide valuable insights that help identify opportunities.
This said it’s no surprise that companies all over the world are increasing their investments in software solutions that deal with great amount of data. In this article, we’ll clarify what is Big Data and how it can help solve business problems. Hope you enjoy it!
Big Data is a term created to describe the tools, algorithms, and structures used to manage and analyze extremely large sets of data, both structured and unstructured. Companies can then use these datasets to build predictive models and extract business insights from it.
Big Data analysis can help uncover hidden patterns, market trends, customer preferences, unknown correlations and other information associated with the company’s interests. This can help build more efficient strategies in all departments and increase revenue, resolve problems, boost productivity, and so on.
The most used tools for building a structure that handles Big Data include Hadoop, Apache Spark, and Apache Hive. There are also ready-to-use solutions like Amazon Web Services and Google Cloud.
Now that we have the concept of Big Data uncovered, here’s how a proper analysis can help in decision-making processes.
Key Performance Indicators (KPI) are very important in decision-making processes and help structure a better analysis – and, therefore, build a better strategy. Big Data Analytics not only helps identify these KPI but also delivers more precise information.
Let’s say, for instance, that a company wants to build a strategy based on the number of daily calls it makes to inactive clients.
Collecting the total number of calls is one thing; but filtering the number of completed calls, qualified lead per calls, missed calls and other information can help with a much better analysis.
Having to work on internal measures to boost employee productivity is not an easy process. First, it’s hard to tell what affects productivity. Second, working out a solution that doesn’t focus on the problem can cause more harm than good.
With a proper Big Data analysis, using dashboards and visualization tools, it’s easier to identify productivity bottleneck because the company has more detailed information to analyze.
Once the company has a reliable structure to ingest and store its data, it can be used to build predictive models through statistics or machine learning. The ability to leverage larger amounts of data for building the models will result in more accurate predictions. Having more data also means being able to use modern methods like deep learning, that needs massive amounts of observations to be effective.
Big Data is an important business asset that can help identify and solve business problems. But it’s important to count with the proper tools and resources for an accurate analysis.
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