An effective data engineering platform can help retailers harness this vast amount of data to optimize the customer experience, increase sales across all channels, and make merchandising a data-driven process.
Sales are expected to grow by 3.5 percent in 2017 and e-commerce continues to make massive gains with an expected growth of 15 percent this year (Kiplinger, 2017). Tied to that, data volumes within the retail industry are growing and the pace of that growth is accelerating.
Sensor data, log files, social media, transaction data and other sources have emerged, bringing with them a volume, velocity and variety of data that far outstrip traditional data warehousing approaches. Proactive retail organizations harness these new sources in innovative ways to achieve unprecedented value and competitive advantage in an industry space.
Five use cases to better understand the value of big data analytics in the retail industry.
Optimize asset utilization, budgets, performance, and service quality.
Data engineering platform that quickly transforms businesses into agile, insights-driven organizations.
Datameer vastly accelerates your time to insights about customers, offerings, operations, and investments.
From a business standpoint, retailers will need to empower people across their organization to make decisions swiftly, accurately, and confidently. The only way to achieve this is to harness big data to make the best plans and decisions, understand customers more deeply, uncover hidden trends that reveal new opportunities, and more.
All of these priorities require data engineering that drives action. These tools can rapidly bring together and explore massive sets of structured and unstructured data to uncover hidden patterns, new correlations, trends, customer insights, and other useful business information.
Integration — The platform contains more than 70 out-of-the-box connectors and has easy wizard-led integration of any data type, size, and source, eliminating the need for ETL.
Preparation and analytics — Datameer provides a familiar, Excel-like spreadsheet interface that includes more than 270 pre-built analytic functions – from joins to complex analytics — for preparing the data set and discovering the insights. Advanced functions like automated clustering, decision trees, recommendation functions, and column dependencies are available with Smart Analytics™.
Visualization — Using a drag-and-drop design interface with over 30 visual widgets – plus a free-form infographic designer for stunning custom visualizations – carriers can annotate results and share them on any browser or device.
Operationalization — Using a combination of management, comprehensive governance, and advanced security functions, carriers can ensure trusted data and analytical results are readily available to the right people based on their roles, and people across departments can cooperate around data with ease. Data and analytical insights can also be fed into core business processes to drive enterprise-wide business results.