Big Data and Business Intelligence in 2017 – The Way Forward

Recent surveys from industry experts portend developments in the field of Business Intelligence and Big Data on all fronts. They foresee several prominent trends in the areas of discovery, collection, collation, analysis and consumption of data, all in the near future.

The Business Application Research Centre (BARC) recently came out with its annual BI trends survey for 2017. The BARC survey was carried out on 2800 BI professionals and its results point to a rapidly increasing demand for data management, analytics and business intelligence. Or to be more specific:

  • Data Discovery and Visualization
  • Self-service Business Intelligence
  • Data Quality and Master Data Management

The results of the survey point to databased processes and data-driven business models turning increasingly importantfor organizations in the financial context. Therefore, come 2017, here are the key developments in store for the industry.

Key BI and Big Data Trend Predictions for 2017

  • Challenges in Data Quality and Governance

Organizations seem to have woken up-to the fact that well designed dashboards or presentations are not worth their time if they are based on flawed data. Business intelligence cannot be effective in the absence of data integrity and assured quality. These require ample time, money and effort.

The present challenges include bringing together, collating and analysing data from a wide range of increasingly different platforms. Real-world data is being gathered in a variety of different formats, often highly unstructured – containing textual or other nonnumeric data – making collation a gargantuan task.

This assumes even more importance in the context of heightened privacy concerns and measures like the European General Data Protection Regulation (GDPR). It will bring on more stringent requirements in the year 2017, such as “right to be forgotten” and strict penalties for non-compliance.

  • Evolution of BIPlatforms

A combination of big data, cloud, AI, and IoT technologies can enable businesses to overcome barriers on data access and mining to generate useful insights. All these will entail increasingly complex systems, including the use of cognitive interfaces, machine learning technology and even AI to provide business users powerful insights they require.

In 2017, these technologies are likely to play a major role in broadening the types of data that can be analysed, access to such data and higher levels of sophistication for the resulting insights. Cloud and IoT will play an increasingly prominent role in the collection and collation of data, which in turn forms the base for machine learning and AI to perform analysis and arrive at insights. Huge volumes of data and highly intensive computation requirements will make the cloud imperative for organisations of any scale.

Big Data and Business Intelligence technologies will mature and be increasingly integrated into traditional analytics platforms from major vendors. Organizations no longer want multiple products to take care of their data discovery and enterprise reporting needs. They demandunified BI platforms that support multiple BI use cases and user types.

  • Self Service BI – Reduced Manpower, Higher Skill Sets

Today’s business users are demanding more comprehensive big data solutions than ever before. World over, IT departments are struggling to cope with the steadily growing demand from end-users for newer features and faster implementation of solutions. Enabling such ‘self-service BI’ for the business user community benefits organizations as a whole. In self-service mode, data discovery, visualization, and predictive analytics are the key functions most in demand.

In the year 2017, accelerated advances in aforementioned complex technologies can result in more user friendliness and a trend towards further democratization of data analysis; i.e. doing away with the intermediary – the technologist.In terms of discovery from governed data, most of the activity will shift from IT to the business user. Upcoming BI environments will empower business users to access, share and act on BI content on their own, while IT will be relegated to oversight, ensuring that the published content is accurate and based on data with integrity.

This will result in significant reductionof the time and complexity that users face in accessing and preparing their data for analysis. Consequently, business users will face the challenge of upgrading their skill sets. They will have to move up from simple analysis of relatively small amounts of data to the manipulation and insightful analysis of an exponentially larger amount of data. In order to perform these increasingly complex operations, necessary training will be required at the business user level.

  • Across the IndustryDeployment

As the field of BI has grown considerably in the recent past, varied businesses and divisions have been increasingly adopting it at an accelerated rate. This was evident in the BARC survey that showed a surge in BI usage in production and operations departments, which grew from 20% in 2008 to 53% in 2016. In addition to the Financial Sector, which continues to be the mainstay, other biggies like Manufacturing, Consumer and Pharmaceuticals too are set to adopt BI in a huge way.

The pharma industry in particular has been successful in leveraging big data for several revolutionary advances in its field. For instance, Japanese pharmaceutical company Takeda uses data readings from mobile phones to deliver health services in some of the remotest parts of Kenya.They have also made significant achievements in BI by solving numerous challenges encountered in the process. Pharma companies routinely face the challenge of handling data from disparate sources that include third party companies, field sales executives, medical professionals, clinical trials, and sales reports. GlaxoSmithKlinehas tied up with F1 Racing’s McLaren Applied Technologies team to employ online big data technology for clinical research in biotelemetry, the remote and continuous assessment of physical and physiological characteristics.

So what is in store for 2017?

  • Data and Governance – IT will relinquish the handholding of businesses and get back to what they do best – designing and delivering solutions that empowers organizations to innovate and shape the future.
  • BIPlatformsData and Analytics will go hand in hand, and companies will look to develop all-in-one solutions for data collection, preparation and analytics.
  • Self Service BI – Collaborative analytics is all set to take centre stage as governed data becomes more accessible and easily shared. Business users will be able to build on each other’s work and arrive at answers on their own.