The idea that Big Data is a magic key for any business is very popular. We decided to figure out what to do with the company, which decided to introduce this popular tool, and how to do it effectively.

What Is It all about?

Big data (BD) is a huge amount of info that helps you to detect hidden patterns and use them to improve effectiveness. For instance, it can be used by Philip Morris to sell more goods or all online casinos on Casinority.com to attract the specific audience.

The information is received by the company after “running” the data through an algorithm. It must be verified by an analyst or specialist in the relevant field of human activity (for example, medicine), which can be used to change the processes in a company afterward, particularly aiming to obtain more profit or optimize costs.

How to Use It?

There are already enough cases about how this tool can be efficiently used. For instance, Microsoft and Siemens developed a “smart” X-ray machine. It takes a picture and sends it both to the cloud and the doctor for evaluation. In the cloud, there is an algorithm for analyzing images built on artificial intelligence that processes the resulting image. The doctor and the system are simultaneously diagnosed; if there is a big distinction, the doctor is notified to double-check the diagnosis. Sometimes it happens that the system makes the wrong decision, but often it helps to see hidden things that people did not notice.

Kodisoft uses BD processing technologies in its interactive dining tables, thus studying clients` preferences and giving them a more accurate recommendation. In retail and distribution, BD allows detecting the connections between the demand for certain goods and the weather or activities over around.

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How to Start?

Start from the correct goal setting and the info collection. “Making money with big data” is not the goal. The goal may be to optimize a certain expense item, increase profits or sales, depending on what your firm produces and what disadvantages it has. Ideally, the firm should have two people engaged in the gathering and analysis of data: an analyst who will build a machine learning model and an engineer who knows how to build data.

Technically, the same solution for working with big data can be implemented on all existing platforms (Microsoft, Amazon, Google, etc). The choice depends on how flexible a system you need should be and how much are you ready to spend on customization and support. Even if you can not yet define the purpose, it makes sense to gather data anyway. After all, when the task is clear, the algorithms will still need the info for analysis, and it should be as much as possible.

For each business or even a type of activity, the profit from BD is diverse. The key point – Big Data allows you to release human resources for more complex and creative work.

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