Data Acquisition and its phases

Data Acquisition

Are you a data science student or an expert? You might have come across the term data acquisition. Data science is mostly related to data acquisition because every time you deal with the data. Data scientist’s job is to procure unstructured or semi-structured data and give it a proper format. This procedure is only possible through data acquisition. Let’s see what is it?

What is data acquisition?

Data acquisition is referred to as the process of collection of data and process it through different methods to store it into the data warehouse. These steps may be collection, cleaning, and then storing. It is based on the velocity, variety, volume, and value. Our basic goal is to focus on value while being a data scientist. Looking forward to becoming a Data Scientist? Check out the Data Science Certification and get certified today.

After apprehending the above definition of data acquisition, you might be able to consider it the procedure for data science. Let’s have a look at the steps of data acquisition.

Phases :

Manual procedure to improve the performance and quality of the data is tiresome and may increase the burden of work. You might get tired after measuring the huge volume of data. You have to put a lot of time to carry out the job. So, to increase the ease of store data and increase performance, we can divide the whole process of data acquisition into six phases. These are discussed below as:

Select category:

The first phase is to hypothesize the category of your data based on your personal information and other relevant cases to the data. This will help you properly classify the data into various categories and choose the one you are looking for. Hypothesis will help you approach the data effectively. Also, check this Data Science Chennai to start a career in Data Science.

Develop a list of data provider:

Data Source is essential to determine whether the source is significant and relevant to your purpose or not. Find all the potential data providers and make a list to appreciate it. Move to the next step to improve the list.

Data provider due diligence:

While handling and saving data, all the data forms and their potential providers may not be of your interest. You need to eliminate those and select the ones that matter to you. Data provider due diligence will help you find purposes and select the right one for your data. Become a Data Scientist with 360DigiTMG Data Science Coaching in Bangalore. Get trained by the alumni from IIT, IIM, and ISB.

Data provider Test :

Your business needs to test the essential qualities of the data provider. It determines the purpose of your data and makes your choice more selective and serious. You must go for this procedure to find out the aim of your facts. Want to learn more about data science? Enroll in the Data Science Course in Pune to do so.

Calculate ROI :

Once division is done and data is processed through the above four steps, the next step is to find out the ROI. You can do this step effortlessly but is highly influential for data acquisition. 

Integrate and produce :

Your ultimate purpose is to collect data, clean it, and produce it for business ambitions. Once you have done all the above steps, you need to do the last. It includes integration of the data provider to the production pipeline to store the data.

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