Big Data Learning: What are the seven key steps to extract big data?

In the daily work of big data analysts, extracting data is a very common job, but different people have different results. If the analysis is biased towards the needs of enterprises, it is difficult for data analysts to succeed in big data projects. Today we will learn big data and extract big data 7.

What are the key steps? Teach you to refine big data gold. To this end, Bian Xiao has the following suggestions. Let's have a look!

1. Start with traditional relational database data.

This is the data stored in the columns and rows of SQL or other relational databases, which can be easily queried by users. If you are selling, you can start to look at different products, see where and to whom how many products were sold, how many products were returned, inventory level and so on. Based on these data, we can establish many relationships in sales, inventory level, customer location, service records and so on. Because there are too many data related to sales, sales is an easy field for enterprise users. It is very easy to add big data in this respect, which can improve the depth of the query, so that you can really find the elusive gold you want.

2. Add big data to an existing relational database query.

Once the company knows the sales data of the relational database, new problems will certainly appear. A company may see a surge in sales in an unexplained time. These sales peaks are abnormal, so the company decided to add some big data to its relationship data to understand what is happening. One of its big data choices is to introduce weather information, which may be introduced as an XML data stream. The company found that on cloudy days, sales tend to surge, which may encourage people to shop. "

3. Gradually add more big data to the query.

By adding big data to the traditional sales query data, the company has now entered the field of big data. From here, you can easily add more types of big data. The next logical step in the sales report may be to add comments from customers and others about your product. Once you start asking questions about sales and realize how certain types of data can help you better understand your business, you can easily add them to big data sources.

4. Train your employees step by step

Many companies lack the skills needed by data scientists and big data analysts. It is a very attractive way to start with relational database data and then gradually expand to add different types of big data. You can gradually increase employees' understanding of big data. In this case, tools and consultants can help you as needed. But when your employees start with a relational database that they already know very well, it's not a big leap to start using big data. They supplement and expand on this basis.

5. Consider the mixed reporting environment of data

Once you start adding big data to relational database queries, you need to define another data repository for these data. Unstructured big data cannot reside in a relational database. What you need to do is to define a big data database and move the combination of traditional data and big data into this big data database. The good news is that you don't have to spend new money to buy new servers and storage devices. There are many cloud providers that can host data in Hadoop or other big data databases for you, and they can also manage these data. The best news for companies that are still trying to make business sense from big data is that they can gradually transfer their business and IT personnel to productive big data projects by starting with traditional databases. And the basis of the report that everyone is already familiar with.

This can ease the anxiety of business users and IT personnel, because they can start with what they know. When you enter a more ambitious big data project, it also reduces the risk of failure.

The above is the "Big Data Learning: Extracting Big Data 7" that Bian Xiao sent to you today.

What are the key steps? "I hope it will help you. So, how do we start learning big data? If you are interested in big data engineering, I hope this article can help you. If you want to know more about the skills and information of data analysts and big data engineers, you can click on other articles on this site to learn.