Over the last 20 or 25 years, there have been significant investments made by companies in infrastructure to improve the ability to connect data across the enterprise. Any part of the business is now able to collect data. Even some parts of businesses are more equipped to collect data like marketing, manufacturing, supply chain, customer management, and so on.
“We can’t become what we need to be by remaining what we are.” – Oprah Winfrey
With this transformation, data is now easily available and that is leading to extracting more and more useful information and knowledge from it.
In the early phase of this change, firms could have statisticians and analysts manually explore the data and extract meaningful information from it. Now the things have phenomenally changed. With the increase in the data with its variety and speed, it’s gone out of human capacity to analyze it, and that is taken over by easily available computing and processing power through cloud technology.
This has enabled broader and deeper analysis of data than previously possible. At the same time, the algorithms that convert data into insights have significantly improved allowing the development of widespread business applications of data science.
Marketing, finance, telecom, and retailers have been at the forefront in capturing and utilizing the data. Online advertising targeting the right audience, and managing customer relationships have been in practice for a long time now. Similarly, in the finance industry, data has been used for credit scoring as well as fraud detection and automated workflows. Large retailers like Walmart have been effectively managing supply chain, product recommendation as well as personalized marketing and communication using data.
The ability to capture and use the data is now percolated to small and medium businesses irrespective of their size and sector. Even a small brick and mortar can use the data to optimize inventory and strategies its sales using data.
There can’t be a better time to look at some of the basic principles of extracting knowledge from the data. Let’s discuss how you could use your data and the technology available to make the best out of it through a series of articles.