Small businesses can get away with a few Excel spreadsheets for tracking their operations. However, as organizations continue to grow, they can no longer keep up with that simple method. At one point or another, data begins to pour in, and a single-page spreadsheet transforms into a database that later grows into a data warehouse.

Organizations that want to win on their markets need to know where to find the data they need and how it all ties together. But before setting out to analyze data, they need to make sure that their dataset is clean.

Read on to find out what data clean cleaning is and why it’s so crucial for analytics and business intelligence.


What is data cleaning and why should you care?

Datasets usually contain large volumes of data that may be stored in formats that are not easy to use. That’s why data scientists need first to make sure that data is correctly formatted and conforms to the set of rules.

Moreover, combining data from different sources can be tricky, and another job of data scientists is making sure that the resulting combination of information makes sense.

Data sparseness and formatting inconsistencies are the biggest challenges – and that’s what data cleaning is all about. Data cleaning is a task that identifies incorrect, incomplete, inaccurate, or irrelevant data, fixes the problems, and makes sure that all such issues will be fixed automatically in the future.

According to CrowdFlower, data scientists spend 60% of the time organizing and cleaning data!


Here’s why data cleaning is so important

Data quality is of central importance to enterprises that rely on data for maintaining their operations. To give you an example, businesses need to make sure that accurate invoices are emailed to the right customers. To make the most of customer data and to boost the value of the brand businesses need to focus on data quality.

Here are some more benefits data cleaning brings to enterprises.


Avoid costly errors

Data cleaning is the single best solution for steering clear of the costs that crop up when organizations are busy processing errors, correcting incorrect data, or troubleshooting.


Boost customer acquisition

Organizations that maintain their databases in shape can develop lists of prospects using accurate and updated data. As a result, they increase the efficiency of their customer acquisition and reduce its cost.


Make sense of data across different channels

Data cleaning clears the way to managing multichannel customer data seamlessly, allowing organizations to find opportunities for successful marketing campaigns and new ways for reaching their target audiences.


Improve the decision-making process

Nothing helps to boost a decision-making process like clean data. Accurate and updated data supports analytics and business intelligence that in turn provide organizations with resources for better decision-making and execution.


Increase employee productivity

Clean and well-maintained databases ensure high productivity of employees who can take advantage of that information in a broad range of areas, starting from customer acquisition to resource planning. Businesses that actively improve their data consistency and accuracy also improve their response rate and boost revenue.


Does outsourcing data cleaning make sense?

Organizations that are busy growing their operations often struggle to keep their databases in shape.

Outsourcing database cleaning and management is a smart move. That way organizations can take advantage of extra resources in a low-cost and low-risk way, without adding new data scientists to their team.

Outsourcing data cleaning is a flexible solution – the resources are available right when organizations need them. Moreover, they can also experiment with new ideas without having to invest a lost up front.


Cleaning your data is a must

Businesses that take proper care of their databases are rewarded with these and many more benefits. Organizations that keep business critical information at a high-quality gain a significant competitive advantage in their markets because they’re able to adjust their operations to the changing circumstances quickly.

At Sunscrapers, we know that clean data is the starting point for any successful data science project and always include it to make sure that our projects bring maximum benefits to our partners.

Przemek Lewandowski

Przemek is a co-founder and CTO of Sunscrapers. He’s a graduate of Warsaw University of Technology which lead him to become a software consultant. At Sunscrapers, Przemek is a technical leader who supervises high-quality service delivery, helps to solve problems and mentors other team members. Przemek is a passionate community activist who organises and speaks at tech events and leads open source projects.

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