Today the amount of data generated from different sources is not just huge but tremendous. Ironically this precious information remains of little use until it is visualized and structured properly. So here comes the main task Business Intelligence developers perform - provide insights and fresh view of current trends, binding with up-to-date business situations.
Yes, some investment here is an ultimate must, but after all, it is worth it. Recent Nucleus Research show: every dollar spent on analytics will be covered later on. In other words, the business gets $10.66 for every dollar spent on intelligence development.
However, another research clearly shows: if the company chooses to use all power of analysis, it comes to decisions faster and they are on average more effective.
Why is the business intelligence development needed?
Applying BI development to plenty of domains is a reality now. It is especially true for big retail chains, having tons of data across the stores. So it is impossible to see clearly what's going on. For example, you can suddenly find out that some goods are difficult to store, but are sold once in a while. Thus you experience some loss. Another thing - you might fail to predict the shortage of some goods, and as a result, people start buying them somewhere, not in your store.
All these unpleasant things happen because you don't have all the available data displayed in a simple and effective way to work with. Depending on the industry the cost of your mistakes might become disastrous.
In some fields, for example, aviation, business intelligence can save lives, showing beforehand that some devices do not work well. Business intelligence is used in telecommunications as well, so it is easy to track performance, profitability, create marketing campaigns and many more.
Another point to be mentioned is that business intelligence reporting software can be provided to some state institutions in cases defined by law.
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What infrastructure do you need for business intelligence development?
The most important is to create a developed ecosystem, which would collect data from different sources, among which - CRMs and spreadsheets,
Also, this data should be stored somewhere, so one has to build a data warehouse for organized information or a data lake if there are structured and unstructured data for further use. One way to develop them is to do everything from scratch, another is to use already existing services.
But all the previous steps are of little use if you don't have a good team of developers, who can structure and clear the received data.
The ETL (extracting, transforming, and loading) part is the core process of business intelligence development. It might take up to 80% of the whole project time. Technically only as soon as this part is successfully processed, developers can start working with the data directly. It means they have to possess a certain set of skills and work with such technologies as MS SQL, Oracle, MySQL Hbase, BigSQL Data Lakes, AWS Redshift, SSIS, SSAS, Pentaho, Tableau, QlikView, Power BI, etc..
ETL Procedures in Data Engineering
How to build and use a business intelligence solution?
Focus on the client's needs. Your picked BI software development partner has to work with the requirements that already exist and at the same time perform a profound analysis of upcoming needs.
Another point to be taken into account is tech leads involving, so the partner can see the existing KPIs and act accordingly. Thus the requirements for the customer will be formulated clearly.
As it was mentioned, the ecosystem building is the key. If it is done properly, data extraction and storing become simple and efficient. Thus all the requirements will be met. It is the main responsibility of big data architects - to build stable and reliable on-premises BI solutions, as well as to customize cloud-based ones.
After the BI solution is deployed, the results should be validated as soon as possible.
BI development is about transforming the data, including not just extracting, but loading as well.
Performance of business intelligence solutions has to be optimized in cases when they work with substantial delays, being unable to provide insights when needed.
Pay attention to Quality Assurance services at all stages of the development process. Quality assurance checks if the presenter's solutions are valid. They work on test scenarios to make sure that the data meets the set of existing requirements.
The solution is supported and maintained after the deployment in tight collaboration with the client's team, working with it.
To provide data visualizing the following BI reporting systems are used: QlikView, Qliksense, Tableau, and Power BI.
Data insights are turned into business value.
Any business profits from data, in this or that way. But if the data is just a bunch of dispersed information, it is useless.
To make it work you should have it structured and organized. Don't forget about visualization and proper storage for further needs.
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