Keeping communication lines open and active with customers are few of the best ways to achieve business success. Customer is ultimately the king in any business and customer responsiveness can make or break the future of your business.
This makes customer data one of the most essential assets to build as part of your core business strategy. Now imagine this; you have been making all the significant preparations for an important business deal. You are gradually progressing ahead towards achieving your end goal and miles after reaching your destination you suddenly realize that you took the wrong turn just because of a faulty signboard. Is that fair for you, your organization or your customer even? Certainly not!
You might have huge terabytes of data that you are heavily investing on. Top businessmen, Entrepreneurs, VPs, CEOs and global leaders and other decision makers are all part of your data lists. But, this is just as good as owning a Ferrari without possessing a driver’s license. What’s the point of owning your dream car without being able to enjoy a guilt-free drive?
This is exactly what unclean data can do to your business. The importance of data cleansing cannot be stressed enough. It can cost you heavily and rob you of your valuable business investments and profits.
According to a report by Gartner, bad data causes 40% of all business initiatives to fail. An email send to such a bad database can mean:
- loss of revenue and resources
- lower customer satisfaction
- poor business reputation
- lower brand loyalty
Your ISPs can even get blocked to receivers for this.
Cleaning your database can be a huge challenge especially if you’re thinking of doing it manually. This can just add on to your business woes. Partnering with an expert agency that can run an efficient data cleansing process can fetch you the right results.
A comprehensive data cleansing approach can detect and eliminate errors and inconsistencies present in your database.
The phases in Data Cleansing should ideally involve:
Data standardization – often the first step in the data cleansing process, it establishes a sense of trustworthiness that data can also be used by other applications in the organization.
Data analysis – this involves detection of errors at a comprehensive level. Ideally data analysis platforms should be used to gain metadata about the data properties and detect data quality problems.
Data normalization – this step involves organizing the fields and tables of any relational database to minimize redundancy. It ideally involves splitting of larger tables into smaller and less redundant tables and mapping the relationship between them.
Quality check: quality checks are extremely crucial and need to be carried out at regular interims to ensure optimal data quality.
Data duplication: It is a specialized data compression technique for eliminating duplicate copies of repeating data. This technique is used to improve storage utilization and can also be applied to network data transfers to reduce the number of bytes that must be shared.
If you too are in the quest to ward off your data cleansing worries, your search ends here. Call us on 877-755-0023 and seek an appointment with our data expert team today and discover how you too can translate data into actionable insights with our niche data solutions.