30 Jun Why Business Intelligence Sometimes Seems Like An Oxymoron
Knowing what to do with lots of data can be puzzling. Even with fancy business intelligence tools to do all the hard work, transforming data into something truly useful for making important business decisions can be hard. Often some pieces of the puzzle feel as though they’re missing or don’t fit nicely together, hindering your overall picture of what’s going on in your business – and making your business intelligence tools feel like an oxymoron.
So how can large companies improve the quality of reporting and dashboards that their business intelligence tools create?
It’s quite simple; to get quality outputs, you need quality data. For companies with a lot of important, historic information in disparate systems, the best way to produce quality data is to standardise it. Standardising data helps to improve the accuracy of business intelligence tools running data comparisons.
Quality outputs from business intelligence tools require standardised data that is:
- Accurate – is the data correct? Does it represent the right value? Is it represented in a consistent and unambiguous form?
- Timely – is the data available without delay? Is it the most up to date version available?
- Stored in one place – is the data from disparate systems integrated into one storage place? (eg database, data lake, data mart or data warehouse)
How to standardise your data with ETL
Standardised data involves converting raw data into similar data, by changing various formats into a common format. For example, insurance company client information may be stored in different silos (such as a customer database vs. a claims database), with different identifiers (e.g. name format – ‘Mrs A Smith’ vs. ‘Anne Smith’).
There are a range of different ways to standardise data, but a common method is Extract, Transform, Load (ETL) which transfers raw data from different systems into a common storage place, like a data warehouse, in a usable format.
- Extract: taking data out of a system.
- Transform: converting the data into a format so that it will have a relationship with the other data, and will be easy and useful to produce reports on.
- Load: putting the data into a standard storage area.
Business intelligence tools benefits
Once businesses have standardised their data, they can really begin to reap the benefits that business intelligence tools have to offer.
Large corporations in any industry make critical business decisions every day, affecting their customers and stakeholders. One example is insurance companies needing up-to-date reporting tools for identifying and understanding trends to help them project manage and make strategic decisions around managing risk.
Because the nature of insurance data is both complex and copious, most insurers now use a business intelligence tool to help them quickly assemble all the relevant pieces of the puzzle into a clear, helpful snapshot of what they’re investigating. Business intelligence software sources and analyses the data into reports and models they need for decision-making.
If every time they need information they have to manually extract the data into a spreadsheet, analyse the data, and then get a result and make a decision, they’re wasting a lot of time and resources with a process that can be automated. Accuracy issues also arise when doing anything manually.
Business intelligence tools help people make decisions quickly and ensure accuracy in reporting. Information changes so quickly, so allowing access to it in real-time is also an important application of business intelligence software.
Every good business intelligence tool has:
- Query functionality.
Querying gives users the flexibility to look up any type of information they might want to report on to help answer any business question that may arise. If you don’t have access to the information, you can’t report on it, and you can’t make business decisions around it.
Reporting and dashboards are important so that users can get a real-time snapshot of the information they need to run their business. Likewise, forecasting analyses existing data to make calculated assumptions about future trends, helping businesses to prepare for what may happen in the future.
However, all these great functions could be rendered useless if they don’t have standardised data.
Achieve smarter business faster
Getting data standardised correctly positively affects the quality of your information (and therefore business decisions) across your entire organisation. Having clean, accurate and standardised data means that you can confidently make smarter business decisions faster, knowing that all the pieces of the puzzle will fit together to form an accurate picture of what you require from your business intelligence tool.
To learn more about integrating, automating and extending your business data download the viisConnect brochure ↓