Analytics Lessons Learned: How Four Companies Drove Business Agility with Analytics

Data analytics is an essential part of any business strategy. Businesses, governments and individuals worldwide use data to make responsive, informed and timely decisions using performant data analytics. It’s not enough anymore to set a business goal and work toward it; in order to stay relevant in today’s market, organisations need to have a finger on the pulse of their business in real time.
For most organisations, this means stitching together a multitude of services to run analytics. This approach results in brittle, highmaintenance architectures that drain resources to manage technology, resources that ought to be spent on responding to new opportunities. In the world of analytics, speed is paramount, because the value of data depreciates with time. Think of a scenario where you can predict that a part of a manufacturing line is faulty. If you find this data point early enough, you can perform preventative maintenance and avert any potential damage. Besides speed, organizations also need to have agility and scalability to be able to scale their analytics workloads according to their business context and challenges.