Business Intel. & Analytics

Data Science & Analytics

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What is Data Science & Analytics?

The recent massive growth of data science and analytics was spurred by the availability of massive datasets and cheap computing power. The two fields can be considered different sides of the same coin, and their functions are highly interconnected.

The main differences involve the scope and the goal: the former is more macro-oriented with the purpose of asking the right questions to produce broader insights, whereas the latter is focused on the micro and finding specific, actionable results. The analyst examines large data sets to identify trends, develop charts, and create visual presentations to help businesses make more strategic decisions. The scientist designs and construct new processes for data modelling and production using prototypes, algorithms, predictive models, and custom analysis.

Why is Data Science & Analytics important?

Data science brings together the domain expertise from programming, mathematics, and statistics to create insights and make sense of data. While reporting and business intelligence will always have its place for holistic overviews of any market, company or organization, digging deeper beyond the current or past outlook is becoming increasingly important.

Supply chain analytics

Companies can gather, assess and act upon the data generated by their supply chains. A few examples of supply chain analytics include demand planning, sales and operations planning and inventory management. Each of these activities can increase the overall efficiency of business operations, which can lead to sizeable cost savings. It allows you to make not only quick adjustments, but long-term strategic changes that will give the business a competitive advantage.

Customer acquisition and retention

The use of big data allows businesses to observe various customer related patterns and trends. Observing customer behaviour is important to trigger loyalty. Theoretically, the more data that a business collects the more patterns and trends the business can be able to identify. In the modern business world and the current technology age, a business can easily collect all the customer data it needs.