Your insights, analyses and predictions are only as good as the data that you use.
Like a diet, you have to ensure that your body is fed healthy, wholesome foods or you’re faced with uninvited health issues further down the line. The same goes for your data. Bad data gives way to bad results. No matter the goal.
And nobody wants bad results. Especially those that come with downtimes, customer complaints, or miscommunication. Nor does anybody want to miss out on all of the benefits that come with clean, accessible data.
Industry 4.0, Web 3.0 and the push for decentralisation place data at the core of modern success.
Data cleaning. Data cleansing. Or, data scrubbing. Whatever you choose to call it, going through this vital process is essential to the success of any data-driven organisation. Even more so when ensuring that your data is both prepared and optimised for the best insights, analytics and functionality that your tech stack can offer.
And it’s becoming increasingly evident just how important data and having a data-driven culture is, because according to Mckinsey Global Institute:
- Data-driven organizations are 23x more likely to acquire customers;
- Up to 6x as likely to retain customers; and
- Are 19x more likely to be profitable.
However, as powerful as your data might seem, the results that you achieve depend on how good that data is. If data has all sorts of inconsistencies like incorrect formatting, corrupt files or duplicate items, then prepare to face an ever-growing mound of issues.
Why Data Needs Cleaning
“Data is messy. If you have messy data or effectively unusable data, everything you want to do further down the line with it is not feasible. If your data is not cleaned correctly, you can introduce problems down the line,” says Gabriel Eisenberg, Solutions Engineer at Teraflow.ai.
He adds, “You can almost think of it as a must. Like everyone needs data. Cleaning data is inherently messy. Data is inherently a problem.”
Having data at the centre of any company’s decision-making requires a strong combination of multiple data sources. The more inputs you’re able to get, the better your predictions become.
But because the data comes from multiple sources and in different forms, there is ample room for error. With everything from XML, to CSV files, as well as text documents and spreadsheets, there is plenty that can go wrong.
Working with data means that you might need to pull it in from various different sources to do various things with it and in doing so you could introduce problems, or have problems existing in there anyway.
“It’s kind of a given that you will need to clean data. I don’t think you can really get away from it.”
What Is Data Cleaning
The problems within data can be many.
It can be duplicated or mislabeled. It can be incorrect, or broken. And any issues with your data leaves algorithms and models, and thus predictions, inaccurate and unreliable.
So to deal with all of that messy, chaotic data, data cleaning is a massive requirement.
The process is around fixing or removing any incorrect, corrupt, wrong format, duplicate, or incomplete data within datasets.
And while there are no one-size-fits-all solutions in the data cleaning process, as processes will vary from dataset to dataset, it is crucial to understand the effect that data cleaning will have on your business.
“Data cleaning is the process of getting your data ready, or usable, for an intended task. You might have data you want to use in a machine learning algorithm to predict house prices, for example. Data cleaning involves getting rid of unnecessary or bad data and correcting it in some way or another.”
“By introducing those engineering skills into your data team, you enable data scientists to focus on building models, you empower them to actually work with reliable data, and you don’t insist that they are the ones that have to make the data clean, usable and scalable.
3 Benefits of Clean Data
Ensuring that your data is clean and organised brings far more benefit than just accessibility.
Optimising your data brings about a trickle-down effect, where other areas within your organisation will see added benefit and improvements. For example, by ensuring that you have clean, organised information, you’re able to drive more efficient models, reduce friction and cut-back on error and even risk-associated costs.
Some of the other benefits? Well…
Better Decision Making
Without data being clean and accessible, businesses would be running at massive losses.
Every business has a reliance on customer and employee data to make better decisions. And the accumulation of big data acts as a fundamental pillar to effective decision-making.
Simply put, poor data leads to poor decision making. When an organisation makes decisions based on accurate, accessible data and objective truth, it increases the efficacy of decision making.
Quality data and accurate information gives you better analytics and business intelligence, leading to improved decision-making & execution.
Data cleaning not only improves the quality of your data and thus allows for better decision making, it also has the potential to increase overall productivity.
Cleansing your data means getting rid of outdated or incorrect information, which leaves you with the highest quality information available. It means that your employees don’t have to work through countless siloed and outdated documents and can therefore focus on what’s important.
Having squeaky clean, healthy databases in place allows businesses to ensure that their staff members are being productive with their working hours. This inevitably ends up maximising staff productivity and efficiency.
Increase In Revenue
By working on the accessibility and accuracy of your data, your business will make significant improvements in response rates. That increase in responses and interactions will help with achieving business goals more effectively.
Which, in turn, could mean a boost in revenue.
Clean data makes for better results and greater ROI, especially when delivering targeted and consistent messages to the right audiences and staff.
Your data can also help organisations significantly reduce bounce rates. Data cleansing helps in removing duplicate or incorrect data effectively, therefore affecting the entire experience that your company offers a customer.
To top it off, inaccurate and unclean information can drastically drain your company resources as you’ll have to spend twice the amount of time, effort and investment on dealing with a single client.
The proof is in the data.
Data is driving entire industries to new heights and without easy, clean access to your data, you run the risk of falling behind.
With clean, accessible data, your business has far more potential in an increasingly competitive world.
Our teams of data engineers and data experts can help you put your data in the best place it could ever be. If you want high-quality data that drives meaningful insights: