The Retail sector has seen many innovations in the past. You must have noticed the digitization of product data by using barcodes. They are prosaic little graphics that most of us take for granted today. The use of retail barcodes began in the mid-1970s and subsequently revolutionized different aspects of how goods are manufactured, dispatched, tracked, and sold. Today, barcodes are omnipresent, and we don’t notice them because they are ‘mainstream’ with which we are all familiar. Like barcodes, so many important innovations pass into this mainstream world, proving their worth again & again. So, in this blog post, we’ll have a look at some of the hottest trends in Retail currently.
Efficiently managing the different data sources
Enterprises have been managing data for a long time now. But then, today, we’ve reached a point where the quantity, velocity, and variety of data present in the contemporary organizations can no longer be managed without a major change in the fundamental infrastructure and the concept it uses to govern the data. Enter DataOps – it does for a company’s data what DevOps does for the software development which produces it. Gartner defined DataOps as “The hub for collecting and distributing data with a mandate to provide controlled access to systems of record for customer and marketing performance data while protecting privacy, usage restrictions, and data integrity.” The DataOps nature handles the need to manage multiple (potentially hundreds) data sources and multiple data pipelines with various transformations. Data Science and the scientists who understand Azure DataOps & Aws DataOps become essential components of Retail operations. The result is a new breed of data warehouses, data types, data uses, and the governance of users who access it need a framework to hold DataOps’ potential benefits.
DataOps accelerates analytics for Retail
This DataOps-managed service provider recently engaged with a global optical retail chain. This chain offers optician services with eyeglasses & contact lenses. It faced the need to update & improve various transaction systems across the IT architecture landscape, allowing it to review and update how various users leverage BI data to make more insightful decisions.
‘Traditional’ BI, one of this MSP’s critical areas of experience, whereby data gets stored in Enterprise Data Warehouses (EDWs) in a structured format, is being vividly transformed.
Modern solutions can store unstructured (NoSQL) data such as videos, social media content, voice, and pictures. In the case of this optician, it has the means to hold clinical optometry photography of a person’s retina, for example. Such technologies also lend themselves to agile rapid prototyping and simplify end-user access to data, which can move the decision point nearer to the customers.
DataOps understands the interconnected nature of data engineering, data integration, data quality, and data security/privacy. It aims to help CIOs/CTOs rapidly deliver data that accelerates analytics and enables previously seemingly-impossible analytics. In other words, it offers the enticing possibility of moving closer to the customer.
The path to prescriptive analytics
In Retail, this technology provides the possibility of engaging directly with customers who have done any kind of transactions previously in-store, with a complete view of the transaction history. The omnichannel purchase trail can offer valuable insights into purchasing patterns, allow personalized campaign offers, and drive growth through better customer retention.
The most desirable thing in Retail is to reach the level of Prescriptive Analytics, which proposes actions to benefit from forecast predictions and displays the insinuations of each decision option. The retailers can, therefore, influence customer purchases in line with what they want customers to buy, not necessarily what the customers think they need.
As the retailers have understood the business challenges and the associated benefits, the task is to find ways to devise a modern, future-proof BI solution.
Just as the concept of DevOps started gaining traction, retailers will now have to find ways to implement DataOps.
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Conclusion
Organizations open to exploring how a DataOps model can assist and add further value to the tools and solutions involved with a Big Data program can reap even more benefits. However, this natural, current dynamic has equally massive insinuations for companies that must accelerate internal understanding and related experience and skills involved in transforming the BI market.
ISmile Technologies optimizes your data to be trustworthy and business-ready with its DataOps Managed Service. Our scalable and multi-cloud solutions help businesses accelerate their journey to AI-powered automation and improve data qualityq to enable the far-reaching business potential of machine learning and AI. Schedule your free assessment today.
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