Business Analytics and Data Analytics – What’s the Difference

Larger companies often ask this question. Companies need to know the differences and which analytical field is essential for the company. Each company will provide information and details. It can also depend on the ongoing projects of the company.

Some businesses depend on business analytics; others on data analytics. Like projects, businesses, too, depending on what kind of company it is. These two analytical patterns process data to provide results and solutions to clients and companies. And each process will have its team

What is Business Analytics?

In simple words, business analytics is collecting and analyzing data to give data-oriented results based on facts and practical. These results will come with solutions that the company can implement. Business analytics can help companies deal with financial problems and business deals. It can also help the company strategize its business plans for every session.

Business Analytics is Split Into three Categories or Types:

• • Descriptive Analytics: Descriptive analytics analyse history and past events to learn how to plan for the future. It learns from past events and lists out plans used, how they were implemented and so on. It is a process that tries to learn what happened in the past.
  • Predictive Analytics: The data from descriptive analytics is then used by predictive analytics to help create strategies for the future. It cannot predict the future, but it can come up with a list of possibilities. It only gives possibilities after exploring the past.
  • Prescriptive Analytics: Descriptive and predictive analytics finally end with prescriptive analytics. The final type will help businesses come up with possible contingency plans. These plans will apply to all the possible outcomes that predictive analytics has listed.

The process repeats itself at the end of every cycle, although it may produce different results the second time. As it is clearly shown, business analytics is mainly for businesses and companies.

What is Data Analytics?

Data analytics can be called data processing to simplify understanding it. Data analytics scan, explore, analyze, categorize, organize and store data. The data is then used to make decisions that can be according to the current trends. The process helps businesses make informed decisions with a lot of data to back them up. The data that is analyzed will often belong to a company. Companies are known for storing a huge amount of data.

Data analytics is valuable when it comes to organizing, scanning, and storing, all this data. But most importantly, it can use the data to find a pattern – a trend. Once the trend is found, they can use that information to create new products or services. And these products will be successful because they are in trend or will become a trend.

There are different tools that data analytics uses to make the entire process easier. These include machine learning, text mining, big data analytics, predictive analysis, and data mining. All these tools will help scan more data while keeping it organized and ready for use.

Difference Between Business and Data Analytics

Now that you know which analysts do what, it becomes easier to find the differences between the two. Both types of analysts deal with data. Different types of data. Business analysts look at past data meaning what has happened in the past. Data analysts look at both past and present data. So they work with the same material, but they use it differently.

Business analysts are problem solvers. They scan through the past and come up with solutions for the present and probable solutions for the future. They are responsible for sharing all the plans they come up with, with the entire company. The company will most likely use all its strategies that result from scanning data for changes in the company if needed.

They are responsible for organizing and planning the entire process of change. They become a link between shareholders of the business and the business itself. Business analysts also do regular checks on the company for any problems. If they find one, they must find a working solution and implement it as soon as possible. And the entire process repeats itself. They help the business stay intact.

Data analysts are not as responsible for the company as business analysts are. Data analysts scan data to find trends. They then turn these findings into an easily understandable format for companies and businesses. These findings are used to predict trends that may happen. These predictions are then used to create products that will be successful according to the trends.

Aside from translating complex data for the company, data analysts also spend time trying to create new data accumulation methods. They may have a team of data analysts but having innovative technology helping can speed up the process and help them collect more data, meaning they have more accuracy with their predictions.

To see this difference more clearly, we can sum up everything we know about business analytics and data analytics. Business analytics use data to develop possible events and solutions for future and present events. Data analytics look for data that can help them discover trends. It also looks for more ways to accumulate data. So, business analytics uses data to achieve a goal, while getting the data is the goal for data analytics.

Conclusion

These two fields of analytics are not easily understandable. But when simplified, they can help interested parties understand more about the world of analytics and the business sphere. Both these analytic fields, in the end, work for business purposes. Although their goals are different, they both help businesses. They are not that different from each other. Often they are used together to get a better result.

Learning about their roles in a business can also help them understand their differences better. The above mentioned are just a few numerous roles and responsibilities these analytical fields have. Those working in these fields also need experience communicating well and simplifying data for common understanding. They also need to think logically and have a mind that readily analyses things. Without all this, analysts cannot do their responsibilities well.

All mentioned here is slightly more than just the surface of all information on these two analytical fields. Doing an in-depth study of each can even help you decide which one to take as a career path. If interested, this can be the starting point with all the basic concepts and information.