How to improve business decision making with real-time data

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Technology provides businesses with real-time data analysis . This enables them to make correct and, therefore, profitable business decisions . Learn expert recommendations and how to use real-time data integration to boost your business.

Successful business decisions: the importance of real-time data
Currently, many business owners have up-to-date but limited knowledge because the technological tools they employ do not provide sufficient real-time information from sources outside their local business units.

Furthermore, conventional analytics and business intelligence techniques provide predictive data based on static situations since they have not been designed to generate real-time connections or to be appropriate to changing contexts.

To promote successful business decisions , companies must improve the distribution of internal information by using real-time data integration techniques that make information immediately accessible throughout the organization.

Furthermore, the use of real-time analysis based on UK Phone Number Lead artificial intelligence, machine learning and optimization techniques is required.

The first step to achieving these benefits is to ask yourself whether your customer service, HR, supply chain or sales department knows what is happening in your company at all times .

The fact is that, many times, employees only have visibility of the data that is generated or stored in their area, which generates a lack of understanding of the conditions or events that occur in other departments or locations, suppliers, partners or markets.

Part of the solution to this limitation is the use of real-time data integration to provide connected, contextual and continuous intelligence throughout the organization and its ecosystem.

In short, real-time data and its integration allow :

Connect disparate data sources . In a large enterprise, sources might include 500 or more disparate applications and databases; thousands or millions of Internet of Things (IoT) devices; and multiple external web sources.
Analyze contextual and historical data . This can include data about customer interactions, location, sensor readings, IT metrics, copies of transaction data from other departments, and any related external social media, weather, news, or market data.
Have a system of connected applications that run continuously – 24/7, or at least during the workday – so that users can respond immediately when events occur.
Technology for making business decisions in real time
Although successful business decisions require sharing and analyzing data in real time, they must be able to be combined to obtain information with added value.

Active intelligence uses two techniques not found in traditional analytics and BI systems: stream analytics and prescriptive analytics . These techniques help companies redesign decision making.

Below you will learn about 2 cutting-edge tools that use these techniques :

Stream Analytics for smart business decisions
Unlike most analytics and BI software that operates on data at rest, stored in databases or analytics tools, Stream Analytics performs streaming analysis by processing data incrementally and immediately as it comes in . In other words, it processes data in motion.