Education & Training
businesses oſten make ad hoc data connections and think in the short term. But for any business, a data infrastructure, which isn’t streamlined is a ticking time bomb, a problem which is going to get worse. At some point, everything will get very complicated, very fast. Data leadership needs to be just as agile as the technology itself Just a few years ago, it was normal that data engineers would
build a pipeline and deliver data sets almost in isolation. Te people building the pipeline would oſten not have any understanding of the business intelligence they were working with - and the professionals were not expected to know, as well. Business intelligence analysts would then work with the data to
create reports and visualisations based on the data sets that the data engineers provided. Tis was largely a side effect of cumbersome old technology, with data teams working with on-premise databases and data warehouses, which were difficult to scale, cumbersome and required teams to build and maintain their own data infrastructure. Tis ETL (Extract, Transform, Load) process of dealing with
data involved on-premises equipment, and meant that data analysts oſten needed to reverse-engineer operations aſter they happened if the output wasn’t useful to the business - a complicated, long- winded, and expensive process. Just a few years ago, a huge part of the job of dealing with data
was engineering just to get data into the right condition where it could be worked with. Tis had to happen before companies could perform any modelling or work with tech such as machine learning and artificial intelligence. Companies needed lots of employees with differing skill sets just to get access to their own data.
How data warehousing has changed Cloud-based ELT technology has made companies more agile when using data, compared to this older approach - but to take advantage of the potential of the technology requires leadership to be similarly agile. Data leaders need to not only understand the technology but evangelise for it within the business. Te benefits can be seismic. ELT gives businesses the chance to extract value from data far more rapidly than was previously
possible. It means that businesses can analyse much larger pools of data, at far higher speeds. Tere’s no delays in the forms of maintenance or long waits for technical teams to do their work. Tat means that the jobs of data engineers and data analysts are changing. Now more than ever, data has the potential to be
transformational for businesses. As real-time or near real-time analytics become more accessible, the way organisations approach data warehousing needs to be more agile than ever.
The impact of the cloud Cloud data warehouses have changed the paradigm. Business intelligence platforms allow teams to create powerful reports and dashboards far faster than was previously possible. Augmented analytics using machine learning and ‘no code’ ELT platforms have raised the bar in terms of how easily data can be integrated into a business, without requiring gruelling technical work, coding or specialist teams. With the job requiring far less technical heavy liſting, there’s
now a crossover of data engineers and data or business intelligence analysts - an analytics engineer. Previously, there was oſten a gap when it came to understanding
the business value of the data. But a new breed of experts are helping to bridge that gap. To an extent, all the jobs in and around data are changing.
Engineers are now expected to have a little more business acumen than they once were - and business analysts are increasingly expected to have skills such as SQL. For businesses hoping to use their data effectively, it’s increasingly important to hire such employees as data leaders, helping the whole organisation focus on data effectively.
How to become a data-driven organisation Going forward, businesses need to hire data leaders who have the vision to make their organisations data-led, combined with the technical know-how to fully take advantage of the best technologies within the space. Tis isn’t always easy. In data engineering, there’s a huge shortage of people already. Everyone is hiring top talent. With technology advancing rapidly, companies cannot afford not to be on-board with the latest and greatest technology. But the biggest shortage is in
leadership of data teams, because it requires a very specific set of skills and a very specific sort of person. Even now, many people still only understand one side of the equation - the technology or the business side - and organisations need people who understand both. Data leaders need to be people with an instinctive understanding of the technology, combined with the business understanding needed to use data effectively within the organisation. Ideally, they also need to be the sort of skilled communicator who can evangelise for the use of data within the organisation.
30 | August 2022
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