Issue link: https://read.uberflip.com/i/1471966
2 Introduction Data and analytics have unleashed a new era of business opportunity. Fueled by the cloud and ma- chine learning (ML), modern analytics deliver increased visibility across the business, helping to drive decisions that are paying big dividends. Insights culled from real-time and historical data give leadership teams the ability to quickly adjust to unex- pected change, improve customer experiences, become more predictive, and streamline processes for opera- tional cost and time savings. This e-book explores how the growing migration to cloud platforms and services, along with advances in artificial intelligence (AI) and ML, are accelerating analytics initiatives and helping overcome previous barriers to data availability, performance, and scale. 3 Inhibitors to success What's the right mix of analytics? 5 Overcoming the obstacles Machine learning: Capabilities for all 6 How to implement a modern analytics approach 8 Put your data to work 8 Sponsor viewpoint Contents Turning data into business value Here are a few examples of how organizations are already applying analytics for business benefit and the common good: Supply chains are gaining the ability to quickly pivot when market conditions or customer demands fluctuate. For example, if there's a disruption in the partner network, analytics powered by ML alerts net- work members so they can find an alternative supplier or shipper to keep delivery schedules on track. Manufacturers can predictively detect failing equipment and take corrective action early enough to avoid shop floor downtime. These capabilities boost productivity and business continuity, enabling manufacturers to improve production and delivery and reduce costs. Telecommunications companies and other data- intensive businesses are monetizing the data they generate and collect by packaging it and selling it to target vertical markets. In this way, they're creating new revenue streams for their businesses. Marketing departments are using analytics to learn about the likes, behaviors, and experiences of consumers based on their digital footprints. Equipped with this information, businesses can accurately target offers to micro-segmented groups and grow their customer bases. They can also learn customers' preferred ways of communicating and conducting transactions so that their businesses can interact with them accordingly, improving satisfaction and building loyalty. The scientific community is analyzing and sharing huge volumes of environmental data gathered by satel- lites, space stations, and robotic vehicles to inform us about actions we can take to improve human habitability on Earth and enable it on Mars. BUILDING A MODERN STRATEGY FOR ANALYTICS AND MACHINE LEARNING SUCCESS