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Currently business is going through a digital transformation stage that requires management quick reflexes to technology trends and business process review. The main trends include artificial intelligence, virtual and augmented reality, cloud decisions, big data etc.

Data analytics without a rival is one of the main trends. Technologies development is the reason of data quantity increasing. 90% of the world’s data were created during the last few years, and investments in Big Data amounted to $180 billion. According to BARC research enterprises using Big Data have increased their profit by 8% and cut costs by 10%. Beyond that the following  benefits were noted:

• a growth of strategic decisions efficiency (69% of surveyed noticed this fact);
• an improvement of the operative activities control (54%);
• an improvement of customers understanding (52%).

Many companies have already crossed over to digital technologies and generate several GBs of customer data. Such players as Facebook, Amazon, Google are working with big data actively and gaining ground giving priority to the quality of customer service.

In addition, data analytics is a basis for other technologies. For example, artificial intelligence systems learn based on analytics.

Understanding of data analysis and methodology of determining their accuracy gives a possibility to make valid and effective solutions that will lead up business growth and progress. All business solutions must be supported by exact figures and facts that serve the purpose.

Despite the strong performance, there are companies that don’t understand yet how they can start transformation and getting benefits from investments in this sector.

The transformation into data-driven business is a long-term process, that demands investments and following steps realization:

• Work with a right team. Team is the main tool for company’s driving success. Therefore the quality and veracity of the received information will depend on how each team member knows and understands business goals and what data needs to be collected and analyzed for this.
• Goal setting. Before data collection and analysis starting it’s too important to define an overall business goal. If there is one objective – all team’s efforts refer to its achievement.
• Work with correct data. Not all data will be equally useful for business. From all data quantity it’s necessary to identify data that will provide benefit in goals achievement. For start-up company this step has to become priority.
• Right questions. By asking and discussing analytic questions with a team it’s possible to focus on the data type and determine what data is needed.
• It’s necessary to conduct response analysis for useful information extracting. As a result, it becomes possible to make a report whereby business decisions will be made.