Becoming Fernando Alonso

Data - every company possesses it, every organisation seeks to use it as optimally as possible in order to steer their organisation to the winning line, ahead of the competition.

For a moment, consider Fernando Alonso, current Formula 1 champion - but without the Ferrari. Everyone knows that not only would the driver be an average, unknown individual, but the Formula 1 racing event, in all its glory, would also be a non-existing event on the annual sporting calendar.

Data is every company's super racing machine.

Barbara Ohlsson is a business analyst at PBT.

Expanding on this thought process, one would assume that the engineers at Ferrari have already begun applying forethought with regards to the design of the vehicle and how it will change over the next five years, the emphasis always being on winning the trophy, not sharing or losing it.

Technological improvements for faster lap times, reaction times and overall performance are constantly applied. Modifications are made based on data gathered with regards to the vehicle's performance in prior races, based on differing weather conditions, driving styles and road surface changes. Predictive analytics provides input into the future design of the vehicle, and sets the standard for all competitors in the industry. Foresight and planning ensures that Ferrari is and will be viewed as the milestone for Formula 1 racing technology. Do the above tasks associated with achieving success in the industry sound familiar?

Data is every company's super racing machine. Data drives every internal process, every strategic decision, every chess move executed with the view of conquering the opponent. Without data, the organisation would simply not exist. There would be no race to be won, no market leader to compete with or ultimate goal to reach or exceed.

manage and capture it? Will the company's data be a driver to surviving an industry or market crash?

ETL is an acronym for extraction, transformation, load. It is a process that underpins the extraction of data from diverse data sources across an organisation. It applies the framework and tools for enhancing and enriching the data as it passes through the process - applying standardisation, de-duplication, integrity and business rules as the data passes through the channel from extraction to target data storage. ETL is an essential piece of the business intelligence (BI) puzzle.

ETL provides a scheduled and autonomous method of extracting data and applying all formatting and enrichment frameworks, which are developed at the outset of a project and run daily, weekly or monthly - as business requirements dictate. Key performance indicators that have not reached targets are highlighted and flagged as such - thus providing a simplified method for constructing business reporting.

Filters may be applied, and combined output tables can be built to provide business users with essential slice-and-dice functionality. ETL tools provide schedules for running data processes overnight (off-peak hours) and alert support teams to problems with the process - ensuring short turnaround times for data fixes and supporting data availability. ETL tools offer a distinct advantage to any BI department, and are the key drivers for data quality and optimal data processing at all times.

So, if ETL is the solution to ensuring optimal organisational data, then how does an organisation apply predictive analysis? The answer is BI reporting, combined with the insight, skill and business knowledge of both of the BI business analyst and the departmental business role player. Add to this valuable output produced by extensive data mining, mixed with clear business direction and long-term organisational goals. The output of the above mix will reveal the flaws with regards to the current data structures and processes surrounding data capture and storage. Revealing these flaws provides the starting blocks for future improvements for customer profiling initiatives, marketing projects and new product launches specifically designed to appeal to the customer.

Using predictive analysis as the driver, organisations will have the ability to predict the customer's changing requirements, analyse the organisation's ability to respond timeously to changes in the external and industry environments, and move the organisation forward in response to informed decisions for changes to the business strategy. Predictive analytics provides the platform for increased innovation and improved business-customer relationships.

Every organisation competing in the local and global industry today should be investing time, money and human resources in improving the data (and processes surrounding the data) they currently have ownership of. Data is an integral part of driving business direction and strategy forward, and its value - or improvement thereof - should never be underestimated.