As with any project, preparation is key. Data preparation is no different and doesn’t have to be a time consuming, tedious task. If the data is poorly prepared or is taking too much time to bring together, vital business insights will either be inaccurate or out of date. What does this mean for your business and what can you do to solve the problem?
The focus for businesses was very much on reporting, dashboards and visual analytics and these are all well and good providing the data going into them is the right quality and timely. Today, businesses are focusing more attention and investment on this front-end.
New agile vendors in this space are providing businesses with the capability for greater flexibility for business users and less reliance on analysts with coding skills. Added to this, the ability to blend different data sets with lightning speed to save time and resources is adding more value to performance management. Working together Alteryx and Qlik are able to bring this technology to companies and the business benefits are clear.
- Power to the Analysts – today business analysts are being asked to perform more and more data analytics. If your analysts are having to put in a request to IT for the data required and then having to wait a significant amount of time to receive the information, your results could not only be inaccurate but also weeks out of date. The beauty of Alteryx and Qlik is that it puts the power of advanced predictive and spatial analytics in the hands of business users, making the analytics easier to explore.
- Reduces the burden on IT – By giving more power to the business analyst to perform their own analytics.
- Faster data preparation from the data analysts allows the business users to work in a self-service environment using a repeatable workflow. Preparing data can be a time consuming and onerous task but it doesn’t have to be. With the power of Alteryx and Qlik, data can be rapidly prepared, cleansed and analysed using a repeatable workflow.
For further information download the definitive guide to data preparation for Qlik or email email@example.com