Big Data: What is it and how can it help you grow your business?

As much as 90% of the available data has been generated in the last two years. However, the use of data and the need to understand all available data have been around for much longer. The first records of the use of data for business monitoring and control date back to 7,000 years ago, when accounting was introduced in Mesopotamia to record crop and livestock growth. The term Big Data came into use around 2005, when O’Reilly Media introduced it.

Big Data is data that contains more diversity, volume and is retrieved at a higher rate. Simply put, these are larger and more complex data sets that come mainly from new sources. These data sets are so large that traditional data processing software cannot manage them. However, they can be used to solve various business problems.

big data

Big Data and their six “V”

Big Data consists of the so-called six “V”, which define them. These include volume, velocity, variety, veracity, value and variability.

big data


Data volume refers to the size of the data sets that need to be analyzed and processed, which are now often larger than terabytes and petabytes. The volume of data itself requires different technologies than traditional storage and processing options. This means that the Big Data is too large to be processed by a regular processor on a laptop or desktop computer.


The velocity at which data is received and processed is really high. Some smart products with an internet connection work, unlike daily, weekly or monthly updates, in real time. Data rate management is also important as Big Data analysis extends to machine learning and artificial intelligence (AI), where analytical processes automatically find patterns in the data and then use them to create reports.


Variety is about the many types of data that are available. Traditional data types were structured and neatly fitted into a relational database. With the growth of data comes unstructured and semi-structured data such as text, audio and video.

Thus, Big Data also includes a wide range of data types, including the following:

  • structured data (transactions and financial records);
  • unstructured data (text, documents and multimedia files);
  • semi-structured data (web server protocols and streamed sensor data).


Veracity refers to the degree of accuracy of data and their reliability. For raw data collected from different sources, it can be a problem to determine their quality. If this data is not corrected by data cleaning processes, they lead to errors and can reduce the value of business analysis. Data management and analysis teams must also ensure that they have sufficient, accurate and correct data to obtain valid results.


When deciding whether to collect Big Data as a company, it is important to evaluate its added value for your particular business. Not all collected data have real business value. As a result, before using these data in projects, organizations must confirm that the data relate to the relevant business issues they are looking for answers to.


Big Data sets can have multiple meanings or can be formatted differently in different sources – these factors further complicate Big Data management and analysis.

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Big Data and its impact on your business

The development of Big Data technologies has brought companies a ton of information. Previously, BI (Business Intelligence) and analytics applications were mostly limited to structured data stored in relational databases and data warehouses – such as transactions and financial records. Many potentially valuable data that did not fall into the relational form thus remained unused.

The Big Data environment can be used to process, manage and analyze different types of data. The scope of data now available to organizations includes customer databases, e-mails, online click logs, log files, images, social media posts, sensor data, medical information, and more. Companies are increasingly trying to use all this data to support better business strategies and decisions.

Why is Big Data important for businesses?

Before Big Data platforms and tools were developed, many organizations could only use a small fraction of their data in operational and analytics applications. The rest was often referred to as so-called dark data, which is processed and stored but no longer used. Efficient Big Data management processes allow companies to make better use of their data assets, which expands the types of their analytics. Big Data brings more opportunities for machine learning, predictive analytics, data mining, streaming analytics, text mining and other data sciences, or advanced analytical disciplines. This allows you to better understand customers, identify operational issues, detect fraudulent transactions, or even manage supply chains.

The end results can include more effective marketing and advertising campaigns, improved business processes, increased revenue, lower costs, and stronger strategic planning – all of which can lead to better financial results and competitive advantages. Big Data also contributes to breakthroughs in medical diagnostics and treatment, scientific research, smart city initiatives, law enforcement, and other government programs.

What are the business benefits of working with Big Data?

TreeHive Strategy’s Director of Analytical Consulting, Donald Farmer, identifies six potential business benefits:

  • better customer insight;
  • operational improvements;
  • streamlining your marketing;
  • more agile supply chain operations;
  • data-based product innovation;
  • more sophisticated referral mechanisms that are better tailored to the interests and preferences of individual customers.


At a higher level, Big Data brings benefits to companies by generating usable reports that enable them to implement data-based strategies and decisions. It can also direct organizations to new business opportunities, potential cost savings and trends in emerging markets. In addition, real-time analytics applications driven by Big Data can be used to provide up-to-date information and alerts to operations managers, call center agents, sales representatives and other employees.

What challenges does Big Data bring?

Due to its nature, Big Data is demanding for efficient processing, management and use. Big Data environments are generally complex and have multiple systems and tools that need to be well organized to work together seamlessly. The data itself is also complex, especially if the data sets are large and diverse or contain streamed data.

The problems that need to be faced when working with Big Data can be divided into the following categories:

  • technical challenges, including the selection of the right tools and technologies and the design of systems so that they can be scaled as needed;
  • data management challenges, from processing and storing large amounts of data to their cleaning, integration or preparation;
  • analytical challenges, such as ensuring an understanding of the company’s needs and that the results of the analysis are relevant to the organization’s business strategy;
  • program management challenges, which include keeping costs under control and finding qualified staff with the required skills in managing and processing Big Data.

In conclusion

Organizations are increasingly running cloud Big Data systems, using vendor-managed platforms that provide Big Data as a service, which simplifies their deployment and ongoing management. Big Data is a term that describes large, difficult-to-manage amounts of data that flood businesses every day. However, the amount of data is not important, it is important to use it correctly.

If you decide to go the way of analyzing and processing Big Data, which will allow you to move your business forward and create reports that lead to better decisions and strategic business steps, we will be happy to help you along the way. Do not hesitate to contact us for more information.

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