Data as the strategic source for businesses worldwide
• According to Business Insider, 56% of respondents cited enhanced productivity with the utilization of massive data.
• Forbes reveals that 91% of the 700 global C-suite executives surveyed agree that AI adoption will help them outpace their industry rivals and apply strategic data
Why data may be a strategic source for businesses worldwide?
The large sets of structured and unstructured data are complex where regular processing techniques don’t add handling these sorts of data sets. Businesses collect data from many sources such as: sales, social Medias, customer survey or employee number and their payrolls. Storing such sorts of data are big problems for larger companies. Therefore, big data became needs for several multi-national companies. Data strategy is required for the subsequent purposes:
• To began these data and use them in practice
• To clarify top priorities and mention them to succeed in goals
• To know the need of knowledge and the way can it’s sourced
• To drill right down to core business needs and make an achievable plan for future
Here are a number of the uses of datas in businesses worldwide:
1. Understand the market conditions and customers better: Data analysis helps to know current market conditions and trends. For example: by analyzing customers’ purchasing behavior, a business can determine the products that are sold the foremost and style their products within the future accordingly. Businesses can predict what its customers want beforehand and supply them a far better service additionally to raised products. Consistent with Forbes, the pace of investment in big data is increasing, and in 2019 it reached to 91.6%. Businesses can’t only minimize customer complaints by using technological tools but can also increase their business agility.
2. Control online reputation: Sentiment analysis of massive data can detect helps to urge more feedback about who is saying what about companies. This helps to enhance and monitor online presence of companies and re-imagine the company’s vision of knowledge. An AI-ready vision of knowledge recasts and ties it to outcomes versus operations. Rather than merely watching data as a way of showing what happened, it becomes a guide to what can happen and the way it can happen.
3. Save cost: Implementing big data tools could also be expensive within the beginning but it’ll eventually save tons of cash. Big data tools reduce the burden of IT staff, since they’re real time systems. Storing great deal of knowledge is far easier using big data technologies. Moreover, the stored data are going to be accurate because big data tools have greatly reduced the danger of inaccurate data. However, successful implementation of AI and machine learning requires fuel within the sort of data and a gentle supply of it. Without a comprehensive data strategy, organizations aren’t within the position to utilize the competitive benefits of AI adoption.
4. Solve the matter and opportunities: Businesses got to understand what they’re trying to unravel for by the utilization of knowledge strategy. There’s the necessity to know on the character and kinds of success and the easy way to achieve them. The main goals of the companies to use data strategically include: optimization of processes, evaluation of investment opportunities and improve customer experience. The fulfillment of these goals requires its own set of knowledge. For example: Consumer experience might require customer reviews, advertising metrics and knowledge on sales. Similarly, investment opportunities might require market conditions, share prices, rate of inflation.
However, there are various challenges related to the utilization of massive data which will not be solved overnight. A number of them include:
• Data silos increases the information inaccuracy. Consistent with recent report from Experience Data Quality, 75% of companies believe their consumer contact information is wrong.
• Traditional businesses are slower to maneuver on to technological advances and face serious competition.
• Data analysts need to be champion in understanding data from scientific as well as business perspective and are rarely found. Consistent with Cap Gemini’s report, 37% of companies have trouble finding skilled data analysts.