Data quality: What good, clean data can do for your business  

The 7th Investment Data and Technology Summit (IDT) in Sydney highlighted the importance of data and technology in investment management and how companies must understand both in order to stay ahead. 

The summit focused on front-office data and technology use cases and considerations, as well as organisational themes around data governance, technology architecture and business efficiency.

AlphaCert CEO Phil Pietersen and COO Scott Taylor attended the conference last came back with a wealth of knowledge to share with everyone in this space.

This is the second blog in a series where we discuss the key takeaways from the summit. As always, if you would like to know more or explore these topics further, do not hesitate to get in touch.

The importance of data quality

One of the most important points to stress when it comes to data quality is that it is all about prevention. 

The second IDT session highlighted that overall, around 40% of time is spent on cleaning the data as opposed to analysing it. Imagine if the 40% of time cleaning data could be eliminated, and instead spent on faster time to market with new products and quick decision making.

Good data is clean data that can be presented to users with confidence and minimises the need for stakeholders to create their own solutions to deal with it.

Data accuracy and data reporting are tightly entwined: without quality data, stakeholders will not have confidence in the results and will disengage from leveraging learnings from outputs.

If you have the ability to automate the process of data being ingested into an organisation, alongside automated validation business processes that can quickly highlight issues, this will create significant efficiencies before data is pushed to downstream applications. Of course, this requires you to have the know-how to understand the data sets.

Understanding good data, and how to use it

Having quality data is a great thing, but it’s of very little use if you don’t do anything with it. 

This is no easy feat, particularly as not all data is the same – with some of it more critical to the business than the rest. But how do you make that distinction and choose what to use?

Data analytics is technical work. Investing in the know-how, whether in-house or through partnerships, is a fundamental part of the process and key to ensuring your data plays a part in your company’s strategy. How you manage your data is key to the success of the business. 

Reporting on metrics that are meaningful is essential, by prioritising what is aligned with the business strategy organisations can sift through the information overload to ensure business critical reports are the focus.

Boards want to understand how data experts are giving them confidence that the organisation’s data is being managed in an effective way. To answer this, data managers must tell an effective story that aligns with the long-term strategy.   

In the end, good data quality can be measured by the removal of business risk from the operating model. If a business is not operating at its optimal level, it could benefit from automating its data processes. 

Get in touch with us today to find out how AlphaCert can help you gear your company towards long-term growth by supporting data automation.

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