Modern enterprises are increasingly leveraging big data to achieve faster and better business decision making power, and as well as to gain useful insights that can drive efficiency and improve the overall customer journey.
Big data is essentially a combination of structured and unstructured data that is huge in volume and grows exponentially with time. The three aspects critical to big data are the volume of information, Velocity – the speed at which this data is created and collected, as well as the scope – or variety – of this information. By harnessing big data analytics and specifically real-time analytics, organisations can successfully gain insights such as hidden patterns and correlations, user experiences and buying preferences, among others. Real-time analytics, providing almost immediate results, is particularly relevant for initiatives such as the current COVID-19 vaccine rollout.
Big data can be hugely beneficial in terms of knowing who has been vaccinated, what their results are after testing and who else still needs to be vaccinated across the country. The faster this can be done, the better for the country’s health and safety.
Generating better insights
While data is a valuable asset for the modern enterprise, the quality, consistency and comprehensiveness of data that is fed into an analytics platform will determine the value of the insights generated. Hence, the process of real-time big data analytics and success thereof is dependent on Master Data Management (MDM). MDM allows for the accuracy, consistency and accountability of a company’s shared data, which impacts the outcome or result of real-time big data analytics.
MDM is a technology-enabled comprehensive process that equips companies to gain better business insights by providing a single, trusted and 360-degree view of master data assets across the enterprise. Master data is the consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise including products, customers, suppliers or assets.
MDM and big data have a bi-directional relationship. While big data is an enormous amount of unstructured data, MDM primarily uses this information to create trusted sources of structured data throughout the enterprise. Both functions complement each other and both are essential to a modern enterprise that is building a customer-centric business strategy.
Improving accuracy and performance
There are various integration points where MDM and big data collaborate for the purposes of importing and analysing unstructured data to create updated master data and for sharing master data records with big data platforms. MDM improves the accuracy and performance of big data analytics. On the other hand, big data platforms provide and feed additional insights into MDM.
Real-time big data analysis enables an enterprise to move forward with both small and big business decisions in a timely and productive manner, in this way removing operational inefficiency. Operational decisions are mostly based on structured data stored within an organisation, with real-time analytics responding to conditions as they occur, allowing accurate decisions to be taken immediately.
An ideal use case for big data analytics and MDM is social media. Together, these functions provide organisations with the ability to gain valuable insight into customer service, their market and products, based on comments posted on social media platforms. This provides a better and immediate understanding of trends based on customer choices and the sentiments expressed.
Customer preferences are changing very rapidly. To meet customer expectations and to remain competitive, companies must adopt technology that enables customer experience (CX) innovation. It is imperative that companies adopt the concept of MDM and real-time big data analysis, as they not only need to focus on the customer, but also design products and services that anticipate customer needs and preferences.