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Recognizing Vulnerabilities and Risky Behavior Through Business Intelligence

Risk: It is something which every business owner wants to avoid or manage in their life. No matter in which business you are, risk will always be there with whom you need to deal with.

How will you react, if someone tells you that it is possible to get rid of all your business-related risk? Well! At first you won’t believe it, but if it happens, you will certainly celebrate it, right? Businesses in all industries are always surrounded with multiple risks coming from various sources like market fluctuation to catastrophic events like COVID-19. So, if there is a way to reduce such risk, most probably everyone would like to adopt that methodology.

Unfortunately, there is no magic behind this. Companies need to live and learn how to tackle the risk. But it doesn’t mean that businesses should suffer whatever comes in their way. Business intelligence (BI) plays a pivotal role in helping the business understand where they stand and how they can overcome or minimize the risk. It is a general term to gather, store, analyze and give insight data to companies for taking better decisions. In recent years, many tech giants have put their steps in creating smart BI tools for their clients.

By using predictive analytics consulting, BI can help businesses in decision making through valuable insights. Such data allows companies to predict and estimate the future risk and work accordingly. All such things sound like they would make you say ‘Wow’, but before implementation of BI strategy you need to plan it properly. Without adequate planning, you will fail and get frustrated at the end. Keep in mind that BI is a tool and like any other tool, they need smart people to work smartly.

Clean out the information

Injecting any data in the business intelligence tool will never cater to your desired insight. This is one of the biggest mistakes which most of the business owners that try to leverage it commit. Even with customized BI software, doing such practice is insane. Feeding unstructured data in BI can end up with total mess. So, create a strategy, to get desired outcomes.

So, to start with BI, give some sort of structure to your data. Before putting the data into software, you need to clean your data first. It may make you feel like you are taming a wild animal, but consider this: you have heaps of data for analysis, right from the sales stats to the social media posts.

To tackle such a massive ocean of data, some form of sorting is required. Otherwise you will be drowned and eaten by wild animals. Hence, the large amount of data, which needs analysis should be structured properly to meet the predetermined standard. Such a procedure will give a systematic shape to your data and make it easy to model, analyse and forecast. In short, the data will be cleaned to such an extent that you can fetch some valuable insights from them through BI tools.

The benchmark of the cleaning process depends completely on company’s goal. As the process is related to each business profile, you need to work on your own. Below are some points which can help you out with data structuring.

  • Define the objectives which you are expecting from data analysis.
  • Structure the data to meet that objective.
  • Keep in mind the professionals who will use the analyzed data.
  • Find out the best format, in which you need the data.

BI solution integration for analysis

Now it’s the time to work with the BI developers and use the tool for data extraction which you want from the sources. The gathering procedure should keep the relevant information and ignore the irrelevant one. Once done, the tool is supposed to structure the data and finally keep it in the warehouse.

Such a procedure will lead to the creation of a major workflow by taking raw data from sources, converting it into valuable assets, analyzing it and generating deep insights with the companies. This process will provide you with insights in formats like visuals, report or any type as per your choice.  Your workflow approach will be the deciding factor of your BI strategy success. If you successfully cleaned the data, you can expect precise estimations from the BI tool which are as good as predictions. The best part of BI software is, it caters real-time insights which can further reduce the looming risks.

In a nutshell, the complete BI process should answer below mentioned questions:

  • How will the business run in short and mid-term?
  • How can I remain prepared for the risk?

But yes, you should also show your intelligence in workflow planning to achieve better outcomes.

BI software can be your best buddy if you have the knowledge of your business and know how to interpret the results for making best decisions. This software can suggest the steps you should take, but being the decision maker it’s up to you whether you accept it or discard it. BI software can minimize the risk in your business, but you should apply your expertise and experience to take out the best from the data analysis.

Microsoft is still leading in Business Intelligence followed by Amazon

It is believed that Microsoft will continue to dominate in BI because of their advancement in categories like BI stack platform, data visualization product, Azure services and power BI. But no matter how sophisticated BI tool you have, it is needed to have a solid data model, with proficient professionals who can extract most from the business insights provided by BI. If a firm is taking decisions based on poor BI strategy then it’s better not to implement it, as it will lead to more destruction. A successful BI should collect data from multiple sources and render a comprehensive view in a specified condition.

Hence implementation of BI in your business, solely depends on your choice. If you have a skilled workforce who can clean the data properly, then BI tools can be a boon for you. Business Intelligence makes it easy for companies to predict the future risk and remain prepared to tackle it easily.

The post Recognizing Vulnerabilities and Risky Behavior Through Business Intelligence appeared first on SmartData Collective.

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