Episode 750 - August 13 - 2023 - Data and Analytics - Part 1 of 2 - https://dulieuphiendich.com/ và Vina Blockchain

What Is Data and Analytics? Part 1 of 2 From: Gartner.com Data and analytics (D&A) refers to the ways organizations manage data to support all its uses, and analyze data to improve decisions, business processes and outcomes, such as discovering new business risks, challenges and opportunities. • What is the role of data and analytics in business? • What are examples of data and analytics use cases in business? • How do you create a data and analytics strategy? • What is data literacy? • What is data and analytics governance? • What is the future of data and analytics technologies? • What is advanced analytics? • What are core data and analytics techniques? • What is “big data?” What is the role of data and analytics in business? The role of data and analytics is to equip businesses, their employees and leaders to make better decisions and improve decision outcomes. This applies to all types of decisions, including macro, micro, real-time, cyclical, strategic, tactical and operational. At the same time, Data and analytics can unearth new questions, as well as innovative solutions and opportunities that business leaders had not yet considered. Progressive organizations use data in many ways and must often rely on data from outside their boundary of control for making smarter business decisions. Data and analytics is also a catalyst for digital transformation as it enables faster, more accurate and more relevant decisions in complex and fast-changing business contexts. Both individuals and organizational teams make decisions, for example, when a person considers whether to buy a product or service, or when a business function determines how best to serve a client or citizen. Data-driven decision making means using data to work out how to improve decision making processes. This leads to the idea of a decision model, which can include prescriptive analytical techniques that generate outputs that specify which actions to take. Other analytical models are descriptive, diagnostic or predictive (also see “What are core analytics techniques?”). Each can help with specific kinds of decisions. Notably, decisions drive action but may equally determine when not to act. Progressive organizations are infusing data and analytics into business strategy and digital transformation by creating a vision of a data-driven enterprise, quantifying and communicating business outcomes, and fostering data-fueled business changes. What are examples of data and analytics use cases in business? Scaling digital business complicates decision making and requires a mix of data science and more advanced techniques. The combination of predictive and prescriptive capabilities enables organizations to respond rapidly to changing requirements and constraints. The nature and complexity of the problem determines the choice of whether and how to use prediction, forecasting or simulation for the predictive analysis component. The following use case examples combine the predictive capabilities of forecasting and simulation with prescriptive capabilities: • Forecasting the risk of infection during a surgical procedure combined with defined rules to drive actions that mitigate the risk • Forecasting incoming orders for products combined with optimization to proactively respond to changing demand across the supply chain, without relying on historical data that might be incomplete or “dirty” • Simulating the division of customers into microsegments based on risk combined with optimization to quickly assess multiple scenarios and determine the optimal response strategy for each Organizations also use data and analytics in different ways for different types of decisions. Making more effective business decisions requires executive leaders to know when and why to complement the best of human decision making with the power of data and analytics and AI.