In pursuit of growth and competitive advantages, the companies are refining the way they gather business and operational intelligence from data they have on customers, processes, operations, etc. Among many other factors, the quality of this intelligence depends on whether they extract the 'smart data' subsets by eliminating 'noise' or irrelevant data.
For instance, manufacturers have to understand the essence of the gigantic mass of data to correctly evaluate it. They have to know how to remove the noise of the sheer aspect of "volume" and transform it into "quality" information.
The decisive criteria here isn't necessarily the amount of Big Data, but valuable content of the data that is smart.
From understanding data to getting valuable insights
As recent studies show, 40% of large corporations are already running Smart Data projects, and the other 30% are planning to start one. Regardless of your company's activity type, smart data can provide you with valuable insights that will benefit your business. Your objective is to recognize the potential that data provides and to ensure that your company asks the right questions and draws correct conclusions.
Smart Data not only helps businesses understand what is happening at any given moment but also why it is happening. Leveraging smart data allows the companies to make better business decisions, better understand their customers' behavior, deliver smarter services/products, improve business operations, as well as to generate higher levels of income.
Moreover, analysis and utilization of data makes it possible to improve quality, optimization, and efficiency across corporate boundaries and enables customer-group-specific and individualized products to be manufactured.
Why should companies leverage smart data?
All in all, asking the right questions guides the companies to the right, "Smart Data." When the companies aim at leveraging Smart Data, they should begin with the right philosophical background in their data strategies, build the data architecture with the requisite democratization, and create an internal culture of sharing and collaboration.
The need to understand customer behavior is a significant aspect of shifting from Big Data to Smart Data. The consumers are satisfied only when their demands are understood, and sometimes just collecting big data and trying to see what we can extract from it doesn't guide us to the customer intelligence we need. It's of utmost importance to properly filter the information to create manageable streams of data that later on turn into real insights.
How it's Smart Data generated?
The rise of Smart Data projects has his root, in fact, in the failure of many Big Data projects. Based on a recent Gartner report, more than 60% of Big Data projects have not been successful in data-driven insights. And here is where Smart Data appears as a perfect tool to collect, compile, and process these data to prepare it for being efficiently used in generating new insights. Big Data means volume, variety, velocity, and veracity. But Smart Data also means Value.
Smart Data is generated close to the data source, thanks mainly to Edge Computing technologies. So Smart Data is formatted at the collection point, so we transform unstructured and non-valued data into structured and valuable data ready for further consolidation and analytics.
What are the benefits of having a Smart Data strategy?
When wisely leveraged, smart data can help companies effectively manage operational risks, improve product quality, reduce sales-related costs, efficiently track daily production, develop predictive models, as well as test new manufacturing models and make the best strategic decisions. Virtually every social and economic field can benefit from the intelligent use of data.
Transforming Big Data into Smart Data requires companies to identify the sources and data sets that offer value and can be acted upon. This implies to stop collecting vast amounts of all possible data and start detecting what data is missing.