Data Cleaning: Why Your Database Needs It
Modern businesses rely on data and information to be successful. Whether you manage a large, international company with thousands of employees or a small, local business, you’re probably hit with significant amounts of data detailing your operations. However, as time passes that data becomes outdated, inaccurate and needs continual maintenance. That’s where professional data scientists come in! Data scientists spend up to 60 per cent of their time Data cleansing old data so it remains accurate and useful to businesses.
What is Data Cleaning?
As you collect contact information, leads and sales data over time, errors and other issues will come up in those data sets. Data cleansing is the process of removing erroneous records and correctly spelling words with our correct placement convention (e.g., “Fir” instead of “Fire”). The goal is to eliminate problems that would muddy analysis or cause you spend money on marketing. A few examples will help you put this in perspective.
Example 1: As a dry cleaning company, you have an extensive database of former clients. You keep track of the contact information of every company or person that does business with you by having an employee enter it into a spreadsheet or database every time. Over time, this list has grown to be huge! You realize, however, that there are duplicates with misspellings and that street name aren’t standardized. You use data cleansing software to validate address on file, remove duplicates and make sure all the contact information you have is correct when doing this. With the savings from marketing going out to incorrect addresses, it will save you some money.
Example 2: Your marketing strategy is always evolving, and you’ve added more data sources over the years with mixed results. Sometimes inaccuracies are inevitable, but when your cadence starts impacting projects that you communicate with leadership on, it’s time to take a deeper look at this data. You probably found out about some inconsistencies in how you calculate revenue, sales and other performance indicators when it comes to your new data sources. Now your team has two choices: either start working directly with the data source providers to make them compatible or find another solution.
Data cleansing, more technically termed as data scrubbing, is the process of preparing information for use by removing incorrect information and formatting the remaining data in a way that it can be used accurately. Data cleaning strives to not only remove incorrect information and improve usability of data-sets but also enriches the data by completing missing data fields. Data cleansing is a crucial building block for data science; but do not let the name intimidate you. The scrubbing and standardizing process for your data is important for every business, regardless of size or industry.
Why Data Cleansing Is Important?
The number one reason why you should be cleansing your data is that when you don’t do it, your company loses a ton of money. Malicious users and competitors take advantage of this and try to fraudulently misrepresent themselves for your data. You make incorrect decisions based on bad data, and you spend the money you would have saved on marketing campaigns if only you had cleaned up your database before. One of the less-appreciated benefits of data cleaning is that good data can lead to lots of hidden opportunities for businesses. Validating your marketing database, for example, can help uncover new opportunities and produce a higher return on your investment.
The “Why” Of Data Cleansing Can Be Summarized As Follows:
Make More Money: Reduce costs and increase revenue by taking advantage of existing opportunities.
Accurate Insights and Forecasts: Forecasting your sales and seeing more opportunities in your data will help you understand what’s coming.
More Efficiency: Make your employees’ time more valuable by removing the burden of correcting records from them and allowing them to focus on analysis. For small businesses, save time on any data entry related tasks.
The Data Cleansing Process Will Take How Long?
Data cleansing is an important part of your business’s success. The amount of data you currently have, how long you’ve been in business and the resources at your disposal will all determine how long the project will take. Contact cleansing usually takes anywhere from a week to an unlimited amount of time depending on the tool you use. If you have massive databases with mixed formats coming in from your multiple sources, the project can take even longer and become part of your company’s workload.
Having up-to-date, accurate data is an essential part of your company. Data scrubbing will save you money and allow your analysts to work on other projects instead of fixing records. Are you looking for a Data Cleaning Company? Get a FREE Data Cleaning, Data Cleansing or Data Scrubbing Quote from us. For more information drop us an email at firstname.lastname@example.org.
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