Big Data Change

How Can Big Data Change The Life Of A Business?

By Read Dive 3 years ago
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The spread of big data primarily affects business. If earlier enterprises used internal data to improve their operations (sales dynamics, customer base, inventory, partners, communication channels, etc.), now businesses need to use all possible sources of information and squeeze the maximum benefit out of every byte. In addition, analysts in companies often make forecasts for the future based on data from the previous operating year. Big data allows you to analyze data for all the years of the enterprise’s activity and build more accurate forecasts for future periods.

There are many examples of the successful use of Big Data in business. Thus, together with Siemens, Microsoft developed an apparatus for X-ray diagnostics. Unlike existing models, this one automatically sent a copy to the cloud and to the doctor when creating an image. The cloud has an automatic abnormality detection system that uses machine learning tools and is constantly learning. If the doctor’s conclusion and the cloud’s one are very different, the doctor receives an e-mail notification about the need to reconsider the diagnosis. Sometimes, the machine is wrong, but in most cases, it helps to see what a person might not notice.

Any business in any country can conduct a data-driven reorganization starting today. But most will have a question: “Where to start?”. 

  1. To become a data-centric company, you need to start collecting data now, and any information can be useful. It is also necessary to consider that this process must be continuous. The amount of data in the world is growing every minute, and what was helpful yesterday may not be relevant today. Any source of information is suitable for this: the customer base in the CRM system, Google Analytics, social networks, reports on sales dynamics over recent years, etc.
  2. Gathering data is just a tiny step towards a massive data-driven reorganization. To not get lost in the flow of data and not give up everything at the very beginning, it is necessary to learn that big data is for everyone. Be it a small business or a multinational corporation. If it is a small business, hiring an analyst or training some of the existing staff is useful. In large companies, as a rule, analytical departments already exist. Geniusee team will help you make the most of the data you have. They provide a comprehensive data science consulting service to achieve your business objectives by predicting and automating regular processes. Geniusee data science courses will help you increase revenue, maximize utility and reduce costs.
  3. Data has no value; conclusions from it are priceless. The mere presence of data will give absolutely nothing to the company. Data needs to be processed and conclusions need to be drawn from it. As a rule, the analytical department cannot cope with the data for the entire period of the company’s activity. And if you take into account external factors, the process of processing information can drag on for many years.
  4. Working with data is work for the medium and long term. Waiting for instant results from applying is a waste of time. You need to gather your will into a fist and be patient to see the result. 
  5. In a real data-driven company, most employees have all the information about the enterprise. There are several reasons for this: the more open the information is, the faster decisions are made; the analytical department is not overloaded and copes with its tasks; data can be used to solve any operational problems; employees understand what they are doing and can evaluate the result of their work.

“Who owns the information – owns the world”, is a phrase that characterizes the ongoing processes in the world today. However, it is not enough to have information – it is necessary to be able to analyze and draw conclusions. Only then will it become truly valuable.

Becoming a data-driven company is easy and hard at the same time. The easy part is realizing the importance of big data and collecting it. Difficulties can arise from the moment of analysis, interpretation, and implementation of the results in business processes, especially when managing projects for business analysts and data analysts. But today, there are many options for solving this problem. There is a variety of software on the market that works with big data. Also, you can use the services of companies specializing in ML algorithms, which use a more personalized approach to establishing work with big data and self-learning systems for a specific business.

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