Understanding Data Preparation and its Importance

The volatile business landscape has realized the importance of data. Data analytics is shaping the future of organizations by promising more visibility. Henceforth, lower risks and anticipations lead the way toward implementing well-informed decisions. The data stored in phone records, emails, ERP systems, and CRM applications is raw and cannot be utilized for business decisions. This is where data preparation and the role of data experts and scientists come into play.

What are data preparation and its importance?

It is the procedure where raw data from multiple sources is converted into a standard format. The process preparation assures that the data is ready to be utilized by multiple BI (Business Intelligence) tools and systems. Therefore, raw data must undergo analysis and be ready for use in various business sectors.

The importance of data preparation can be determined by the fact that business analytics relies entirely on data. If junk is fed into the system, the data (on which the business or the C-suite determines their decisions) received by the business will be useless as well. Data’s actual power or value rests in how it is acquired, processed, and thereby transformed into actionable insights.

Benefits of data preparation

Some of the benefits of data preparation are mentioned below.

Lesser number of errors

Data preparation is known for taking care of common problems associated with data. This eliminates the possibility of any errors or problems during data analysis. The errors can be handled quickly if any problems are generated during data processing.

Superior quality insights

In the data preparation process, high-quality raw data gets translated into reliable insights. The majority of analytical tools manipulate data to increase its value. Hence, if the data is filled with errors, it gets multiplied after the data analysis. Data preparation assures that the analysis derived from the data is accurate.

Competent processing

Since there are few errors, businesses get to process analytics in real-time efficiently. This indicates that businesses can make better and well-informed decisions in the long run and capitalize on every opportunity.

Tools used in data preparation

There are two primary tools used in the data preparation process.

1.    Self-service data preparation

The experts must have extensive coding knowledge to implement the self-service data preparation. Furthermore, data collection and data cleaning demands have to be executed manually. This indicates that self-service data preparation is time-consuming and tiring. Additionally, the tool is also considered less reliable.

2.    Full-service data preparation

Full-service data preparation offers end-to-end data integration and automation features. Data inconsistencies and possible sources of errors in data sets can be eliminated. Thanks to the custom validation rules and verification processes, since there is no requirement for coding, non-technical users can utilize the tool and deliver solutions.


Every business must understand data preparation, the steps involved, and the tools used. The importance of data analytics is well realized and utilized by a wide array of organizations in different business sectors. There is no one standardized solution for all businesses. Depending on the different business needs concerning data analytics, it will affect the whole aspect.

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