BUSINESS INTELLIGENCE

Business Intelligence

In today's digital economy, everything revolves around information, data and therefore also Business Intelligence. Organizations collect and analyze data in a structural manner to quickly obtain high-quality and fact-based to make decisions. The increasing importance and use of information leads to new developments that will have a major impact on your business. Anyone who responds well to this, and does this a bit smarter and faster, has an edge over the competition. To be able to use that information properly, it is unlocking your Big Data by means of a Business Intelligence solution the most obvious. But a Business Intelligence solution alone is not enough ……

To be able to choose a good data solution, you first need to have a good idea of what you want to achieve with this data. All data touchpoints must be mapped. In addition, it is important to know which data really adds value and which is just ballast. That is why starting with a company-wide Data Scan is a prerequisite. This gives you insight and ensures that you can then choose the right systems. There are many BI Data systems available, but which one suits your organization exactly? Will it be a traditional BI solution, or a more commercial or Ecommerce oriented solution like a Customer Data Platform with built-in BI analysis tools? In short, start with good preparation!

WHAT IS BI?

Navigate through the Big Data forest

Business Data Intelligence is a collection of methods and techniques developed to combat "data overload". It is a collective term to describe a combination of architectures, applications, databases and processes. It enables real-time, interactive access, analysis, and processing of data, and provides the business user with useful information that can be directed. Traditional systems analyze historical data - data from transactions or other business processes - and support the business by revealing relevant connections, trends and patterns in the business process. These insights enable decision makers to make better decisions (fact-based), and end users have access to reliable business information about their customers, suppliers and partners. With this information and insights, the company can respond faster and more effectively to changes in the market.


HOW?

Pay special attention to the pitfalls!

What is often forgotten is that information is only useful if the organization can apply it and actually integrate it into the business process. The biggest challenge for companies that apply Business and Data Intelligence therefore lies not so much in the correct use of the tools and techniques, but in the correct organization of intelligent data systems in the organization. A completely different pitfall has to do with the type of data that is used and the type of analyzes that are released on it. Traditionally, companies use past data to discover trends and patterns. They look, as it were, backwards to determine how the company should be managed. This goes well as long as the road is straight. But there is no guarantee that the trend seen in the recent past will continue. In the current business climate, that chance is quite small. And that is why looking ahead is becoming increasingly important: predicting what will happen and determining the probability of different outcomes. That is called Predictive Analytics.

Specialist in Big Data Analyzes

Developments in the field of BI, Data Intelligence and Analytics are moving faster than ever. Customers demand an ever higher quality of service. The supplier of business solutions cannot escape this either. Simply much more is expected of him or her than just creating a report or dashboard. Ecommerce Result can help you to realize the current investment in Intelligence systems through more effective applications and better integration in your primary processes. This can also mean a scan of the performance of your current Business Intelligence suppliers (the tools and services). In addition, Ecommerce Result can support you in making the transition from reporting and analyzing historical data to Predictive Analytics: predicting changes and trends in order to respond adequately.

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