Data Preparation is the Key to Good Analytics

Featured article by Emily Roberts, Independent Technology Author

The proper preparation of data influences the type of analysis which can be performed with data analytics tools. The less prepared data is, the more difficult it will be for data analytics to be performed and for end-users to answer questions in a simple manner. Also, effective data preparation and modelling has a major influence on the overall performance of a business, so proper data preparation is key for business operations, not just good analytics.

Data preparation can be rather complicated and time-consuming, which is why various businesses such as ZAP exist to take the stresses away. Software such as ZAP Data Hub automates the process of data preparation which saves time, expense and the chance of error. This is highly beneficial to businesses who don’t have the resource, knowledge or time required for data preparation. So, if this is something you know you need to take advantage of, read on to learn more about what data preparation is and how it works.

#1: What is Data Preparation?

Put simply, data preparation is the process of collecting your data and then cleaning it up, consolidating it into one file or table of data, and then using it for analysis. Data preparation is primarily useful where you have messy and inconsistent data. When this is the case, it cannot be analysed properly and could lead to shortfalls within your organisation.

Also, trying to combine data from multiple sources is made much easier when data has been properly prepared. Data preparation is important for any business or organisation which handles a large volume of it, and you should strongly consider having a professional organisation carry it out for you, should you be in a situation where analysis is proving difficult.

#2: Data Preparation Best Practices

Proper data preparation companies use the best practices for data preparation, and these are a hallmark of quality. Some of the best data preparation practices include:

1. Using new technologies and methods instead of one-off preparation processes which always need to be repeated and re-done when new data is introduced;
2. Focus on shortening the time it takes to get business insight through data preparation by applying new technologies and methods which shorten delays; and
3. Carry out a full review of your current data preparation process to get rid of any unnecessary and time-consuming routines.

#3: Why is Data Analytics Important?

You may think that data analytics isn’t important for your business, but it is; this is why data preparation is key. If your data cannot be analysed because it is messy and obfuscated, you will miss out on the opportunity to make key decisions, which could be the difference between success and failure for your business.

With proper data analysis, key business decisions become much easier and it provides you with decision-making insights into areas such as customer trends and behaviour, marketing and overall company productivity. As businesses become more fast-paced and driven by tech, data analysis is only going to increase in relevance and play an increasingly more important role.

As the world becomes more driven by technology and data, the proper analysis of data by companies is going to be integral to their success. By having data that is properly organised and prepared, your business is in a position to have extensive analytics conducted, which can reveal lots of commercially relevant information and help drive the decision-making process.