Like many technology trends, it’s hard to establish exactly when big data became the ‘next big thing’. However, without question, growing numbers of businesses have since jumped on the bandwagon, and many are now collecting and analysing vast amounts of information every single day.
Nevertheless, what many of these businesses don’t understand is that the real value from big data isn’t delivered immediately. No, in order to deliver real return on your investment, you need to be able to take that data and turn it into actionable business insights, and this means the quality of your data is paramount.
It’s no secret that many businesses are working with corrupt, outdated or incorrect information, and what valuable insights can businesses gain if a large percentage of the information they are analysing is wrong? In those circumstances, big data becomes a hindrance, rather than a boon for business.
A Question Of Quality & Quantity
Of course, we humans really are our own worst enemies in the quest for better data quality. False memory syndrome, typos, slips of the tongue and confirmation bias can all negatively impact the quality of the data which we end up analysing. It’s not really anyone’s fault, either. When it comes to completing repetitive manual tasks, people tire, lose concentration and get things wrong.
In order to improve the quality of data being analysed, and in turn improve the quality of insight generated from it, businesses need to eliminate the room for human error while collecting information.
It sounds almost too simple, but automating these data entry processes can easily and dramatically increase the quality and accuracy of business information, particularly with tasks that are traditionally done manually, such as updating employee profiles or transactions.
Automation can ensure that the quality of data is both up-to-date and free of human error, so that enterprises can be confident that they are working with the most reliable data possible. This also has the added benefit of freeing up staff to concentrate on other, less repetitive, activities. Actions that can add further value to the enterprise. In this sense, automation is an enabler, rather than a replacement for skilled staff.
Breaking The Big Data Bottleneck
Aside from boosting the quality of data, automation of business processes also increases the frequency of enterprise data as it’s possible to collect within a set time period. Imagine, for a moment, the amount of data which passes through an organisation in a twenty-four hour window; everything from stock control and sales data to customer feedback through social media. Every single process which relies on manual data entry represents a potential blockage in the organisation.
For example, we could use the analogy of a transport network to illustrate the flow of data around an organisation. More cars, trains and lorries on the road might increase mobility, but if the infrastructure remains the same then the transport network will quickly become congested. This is why we have variable speed limits on many of our motorways. Managing the flow of traffic in this way prevents congestion and ensures the throughput is increased. This is very similar to the way that automation can manage the increasing flow of data within an enterprise.
Unless they are sufficiently streamlined, internal processes can become ‘big data bottlenecks’, preventing businesses from delivering value from their information.
Automation helps prevent big data from clogging up the internal infrastructure of an enterprise, allowing insight to be delivered more regularly. In the case of one well known British high-street store, automation allowed them to dramatically increase the amount of sales intelligence they could generate within a daily period, which had a positive impact on its bottom line.
Automation & Analytics
The quantity and velocity with which data is created is only heading in one direction – up – and that makes analytics and automation ideal bedfellows. Analytics solutions are capable of processing incredibly large volumes of data almost instantly and enable businesses to support informed decisions quickly with real-time analysis and reporting. One such solution, SAP HANA, is in-memory appliance software designed specifically for speed and flexibility.
However, as discussed, businesses need to tune up and control all of the processes that affect their data to get the most from analytics. Without this important step, they simply won’t get the results they want, but rather bad or inaccurate data more quickly.
With automation, enterprises can realise the full value of real-time analytics solutions like HANA by streamlining and accelerating the underlying processes. Only with support from faster, more consistent, automated processes like these can businesses be confident that the data that goes into HANA gets there quickly and accurately. They will also get greater value by automating the way they distribute and access the results.
It’s no longer a question of quantity or quality. Unless organisations eliminate the latencies in their underlying processes, they will continue to struggle to deal with the sheer velocity and volume of big data.