Maximising big data with powerful analytics

The potential to transform business lies with big data, by enabling leaders to make data-driven decisions faster. Organisations will spend $187 billion on big data and analytics technology by 2019, an increase of 50 per cent from the $122 billion invested in 2015, according to the research firm IDC.

By Francois Cadillon, Vice President of Sales, UK, Ireland, and Southern Europe, MicroStrategy, Inc.

New ways of tapping into this potential are being discovered and organisations are able to glean actionable insights. This means they can turn big data into a real-world competitive edge that will help them push ahead of their competitors. Strategies that democratise data and put analytics into the hands of employees across the business, empowering them to make data driven decisions quickly, yield the best results. 

‘Self-service’ business intelligence (BI) is gaining popularity because it enables users across different levels and departments to act on insights and better serve their customers and partners. However, once organisations decide to embark on this approach, many face the challenge of implementing a complete analytics solution that meets the needs of everybody from business users, senior executives, and IT departments. As a result they rely on a myriad of point solutions, forcing them to grapple with data silos, complicated workflows, limited scalability, and lagging user adoption. These challenges, compounded with issues around data quality, poor performance, and unfriendly application design will get in the way of realising the true value of data.

To avoid such pitfalls which only serve to hinder growth and efficiency, businesses must balance end-user flexibility with the performance and governance of a true enterprise-grade analytics platform. To ensure success, organisations must establish roles and processes early, publish a verified system of record, and give business users the power to publish new data and dashboards in a governed environment. Widespread adoption can be driven by considering the needs of the user and then providing access to data via web, mobile, and desktop applications—all using a single, unified enterprise platform. This systematic approach enables organisations to deploy intelligence everywhere, meaning that intuition is replaced by data-driven decisions at every level. 

However, the road to digitalisation is not without its potential pitfalls. By seeking a more data-driven approach, organisations will start dealing with larger and larger volumes of data—making the availability of high-quality data more important than ever before. Unfortunately, the increase in data volume makes it more difficult to quickly deliver data to analysts. That’s where automation through AI and machine learning will prove invaluable. This technology can sift through huge volumes of data and surface the most important insights, thus freeing up more time for analysts to create data-driven strategies and think critically about the business.

Ensuring data hygiene is also a massive challenge for organisations that are democratising data. Contaminated data can be a costly problem that takes significant time and resources to resolve. Minor inconsistencies introduced into data sets can have exponential effects across multiple departments, as users share unverified information with colleagues, clients, and others outside the organisation. Without even realising that an issue exists, well-intentioned employees can make decisions based on faulty data that lead to a waste of company resources, increased maintenance costs, and distorted results.

‘Reverse engineering’ irrelevant, out-of-date, or erroneous data is a tedious, time-consuming process. Company resources are diverted to cleaning up and restoring data to its uncontaminated state, allowing the competition to jump ahead in the interim. Prevention is always best. A robust and comprehensive data governance framework can ensure that every user across the organisation is granted the right level of access to the correct information. This, coupled with employee education, is the best way to ensure the quality of enterprise data and security is maintained.

As companies recognise the potential benefits of implementing a holistic approach to harnessing big data, the use of BI and analytics will become more pervasive. Choosing the correct technology is the key to ensuring that users get the most from content they create while operating within a governed enterprise BI ecosystem.