Big Data and data lake are pretty popular terms nowadays. And even though its big data definition is simple enough, it hides numerous potential advantages for your company. But what are those advantages and how big data implementation and project are looks like? As always, we will answer all these and many other questions. Just keep reading!
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Big Data: Definition and Types
Before talking about complicated projects, let’s start with a definition of big data. As we already told you, it is simple. Big Data is a very large and diverse set of information which is constantly growing. Big data can be both structured and unstructured. When structured, big data is organized in databases and data warehouses. Unstructured data can be defined as raw information collected by a company to understand the needs of its customers. It has no format or model to follow. Big data can be gathered from shared comments on websites and social networks, questionnaires, personal electronics, IoT and so one. There are a lot of potential sources of information.
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Big Data Analytics Implementation Strategy
Big data can become one of your company’s most valuable resources. However, it won’t be able to play its role unless it is identified, gathered, managed and analyzed. To deal with this challenge, you need a reliable analytics strategy. Here are a few recommendations on developing such strategy:
Focus on customer-centric outcomes
Reaching success is impossible when your customers are unhappy. So when starting working on your strategy, prioritize customer-centric outcomes. These mean providing better services and increasing the customer retention rate.
Keep the entire company in mind
Your analytics strategy shouldn’t cover a single department of your company — it should be suitable for the entire enterprise. A strategy must fit the vision of the company and its already existing strategy.
Start with the data which is already available
Before collecting the data, start with the information you already have. It may provide you only with short-term results, but this is still a wise decision. You will save some time and funds, and learn how to work with loads of data.
Invest in tools and skills for big data implementation
The number of analytics tools is constantly growing. Therefore, to create a strategy and implement a project, you will have to choose the most suitable ones. Don’t be afraid to invest money in them — reliable tools are definitely worth the expenses. Besides, make sure that your data scientists know how to use the chosen tools, and invest in their education, if needed.