Here, Brendan Tate takes us on a journey through the reasons why he founded new start-up Cleata Limited, available on the G-Cloud framework
One of the common dilemmas facing organisations is that there is a heavy reliance on data stored in spreadsheets to manage critical processes but no consistent, reliable solution or approach.
Although most organisations have enterprise-class systems, staff and departments still rely on spreadsheets to share, store and manipulate data.
Staff tend to use Excel to fill functionality voids within core systems or perhaps because such an enterprise system does not exist yet – so the department carries on relying on the use of Excel or access because ‘it just works.’
This, of course, causes ICT and Information Management departments issues and disruption such as:
- There is a reliance on data to potentially run critical business processes that is not controlled and managed.
- Data exists outside of the enterprise systems that it should be stored in.
- Data is often siloed, not joined up and inaccurate.
As more data migrates to enterprise systems, a huge undertaking is required to capture the data, review it, and import it.
Data Quality
Data cleansing is not exciting – it is a job that no-one wants to undertake to manually review thousands of records, and it often gets delayed.
Data quality reviews are often given a low priority when there are other priorities and pressures to deal with day-to-day.
Equally, though – data quality is important, if not essential, so how do you balance the two?
It could be that you are implementing an enterprise system and want to validate the quality of the data and improve it before you migrate, but equally another use case perhaps is that you are one of the departments which relies on excel because something better does not exist yet and you share data with your colleagues to keep up to date records.
The spreadsheet-type process is always remarkably similar:
- You email the spreadsheet to your colleague who has the knowledge to update it and return by email.
- You wait for them to check it (and inevitably chase them up for a response!)
- On (eventual) receipt, you have the arduous task of stitching it back to your own master along with the other several versions of the spreadsheet you sent out.
Not only is this time consuming but it can cause risks with version control, files going missing or being corrupted along with the potential reputational damage or breach of GDPR etc.
You only have to look at news reports of what happened with Track and Trace to see how much Excel is relied upon and what damage it can cause when it’s use is not governed properly.
What is Cleata?
I was working on a large time-critical system migration, performing data quality reviews for a client, and I was becoming frustrated with the time it took to issue data to staff to review, chase responses and finally stitch the data back together when it was returned. I needed a solution where I could import the data into a system and then allocate the records out to members of staff with the knowledge to review the records and track progress, but nothing existed.
Machine Learning was considered but disregarded. Whilst Machine Learning works great when you have huge datasets so it can spot patterns when the dataset is too small or too disparate Machine Learning can perform poorly, often requiring significant human intervention. Likewise, if the data is too sensitive or high levels of accuracy are important then this ultimately requires a human to review and clean the data.
The added issue of the pandemic meant that the staff with the knowledge were under immense pressure and did not have much capacity to sit and review records.
I ended up doing it manually line by line, correlating records from various data sources for a total of 190,000 records.
As this problem is not unique to my situation, I, therefore, decided to do something about it. And so, the development of Cleata was outsourced and the company was incorporated in July 2020. Towards the end of the development, I enlisted a couple of developer friends to help finalise the product to ensure it was ready for the market. They are still with Cleata now as we continue to grow.
What can Cleata do?
Cleata allows users to upload their datasets in either CSV or Excel format and allocate records to teams and users to review and update from a central platform.
As a user uploads a dataset a wizard takes them through the steps to configure certain aspects of the file and how it should divide the data up. We have kept the wizard as simple as possible; it is a step-by-step process that allows the user to configure it however they want.
You can:
- Configure column level permissions: Make certain fields hidden, editable or read only at an individual user or team level within a single dataset.
- Divide records based on business rules: Issue and split records equally between teams and users or configure business rules that issue records based on conditions in the spreadsheet such as where column A = ‘ICT’ issue to ‘Team ICT’.
- Track progress via a dashboard and output audit reports.
- Export your data at any time.
You can also set Cleata to issue records in sets over time to ease the burden of the day job.
As users are issued with records, they are notified by email to login to Cleata via a web browser and carry out the assigned actions. Cleata is also mobile responsive. If you have a spreadsheet that requires capturing or reviewing data in the field, Cleata can be efficiently and effectively used for that too.
Cleata is secure: we are cyber essentials accredited, GDPR compliant and we host our data within a secure ISO27001 environment.
As a new start-up, we pride ourselves on being agile, so we work closely with our customers to develop the product further and the functions it offers.
Cleata is a SaaS package and is available on the G-Cloud framework. We also offer a free tier for you to trial the product – just sign up at our website.
