Intelligent CIO Africa Issue 15 | Page 40

FEATURE: BUSINESS ANALYTICS and ensuring customer satisfaction) and defensive (referring to data that helps minimise risk, such as ensuring compliance with regulations, maintaining the integrity of financial reports and limiting fraud). Offensive data activities require real-time analytics to deliver the requisite business insights and value to decision-makers. An offensive data strategy aims to generate customer and market insights, equipping decision-makers with critical insights through interactive dashboards. Defensive data activities largely aim to produce a ‘single source of truth’ by ////////////////////////////////////////////////////////////////////////// 50% reporting directly to the CEO (up from 34% in 2016 and 40% in 2017). Machine learning, cloud enabling data management success Two key technologies are driving the advancement of business analytics that support real-time decision-making in 2018; cloud and machine learning. When organisations move their transactional environment or business systems into the cloud, it provides them with two critical benefits; lower running costs and standardisation. TWO KEY TECHNOLOGIES ARE DRIVING THE ADVANCEMENT OF BUSINESS ANALYTICS THAT SUPPORT REAL-TIME DECISION-MAKING IN 2018; CLOUD, AND MACHINE LEARNING. ensuring the integrity of data flowing through the organisation. Typically, defensive data management strategies aim for control by optimising data extraction, standardisation, storage and access; offensive data management strategies strive for flexibility by optimising data analytics, modelling, visualisation, transformation and enrichment. An effective offensive data management strategy requires the flexibility to produce multiple versions of the truth to suit the needs of different end-users by adding relevance and purpose to data sets: for example, weekly revenue figures that reflect the key insights required by multiple lines of business and can be adapted according to the needs of each. This will prove critical in 2018. Forrester Research predicts that the majority of Chief Data Officers will move from defensive to offensive data strategies, with 40 INTELLIGENTCIO A small team of expert data scientists supported by machine learning algorithms will enable organisations to leverage their data to achieve positive business outcomes. Machine learning can also help rank the importance of data. SAP’s Digital Boardroom, for example, equips executive with real-time contextual information and ad hoc analysis by leveraging lines of business data from multiple sources to provide a single source of truth for the organisation. Since the analytics layer queries directly into the transactional or data warehouse, decision-makers get real-time information on actual business performance, with the flexibility of presenting the information in a variety of ways depending on individual needs. The disconnect between business analysts and the business decision-makers they support has been reduced significantly thanks to the evolution of powerful cloud-based real- time analytics platforms such as HANA. Business leaders in 2018 need to start the journey toward a cloud-based world of actionable business insights leveraging one of their most powerful – and often underused – assets: data. n Forrester Research predicts that half of all enterprises will adopt a cloud-first approach to big data analytics in 2018. SAP’s HANA platform, for example, was brought to market as a database but quickly evolved into a platform that offers organisations predefined data models, predictive services, extractions into industry- standard services, business analytics tools and integration tools. Today, SAP HANA can be deployed on premise or in the cloud, helping to bridge the gap between organisations’ historical data analytics processes and the new world of real-time predictive analytics. Due to the escalating volume of data, organisations are also increasingly turning to machine learning to automate data analytics. There is simply no way a business can afford to employ an army of analysts to sift through data to find value. DUE TO THE ESCALATING VOLUME OF DATA, ORGANISATIONS ARE ALSO INCREASINGLY TURNING TO MACHINE LEARNING TO AUTOMATE DATA ANALYTICS. www.intelligentcio.com