Top 10 Business Intelligence Trends For 2020 and beyond

Gone are the days when data was all spread in excel files and traditional databases within the organization’s context. With the rise of the online age, we have data in social media and cloud-based services that themselves generate tons of data. It is difficult to get an overall view of how the business is performing without having to look for reports in different places. Business Intelligence is all about harnessing the data that a business generates in all its activities and then analyze and visualize this data in order to clearly understand it and gain valuable insights to interpret the performance of the business.

Business Intelligence Trends For 2020

In theory, it sounds quite simple but in practice, it is quite challenging. Therefore, businesses have adopted automated tools to get the repetitive stuff done quickly and focus on the Key Performance Indicators thrown out by those tools. Although, Business Intelligence is not something that is completely a new breakthrough, with the advent of new technologies the trend has changed. In this article, we are going to discuss the top 10 business intelligence that is being focused on 2020 and beyond.

1.Trustworthy AI for decision making

The use of AI tools for making decisions is on the rise and more and more organizations will be channeling such programs either by outsourcing, building, or buying AI services. Business Analysts are concerned about “the trust” for making decisions based on the prediction made by the Machine Learning model and the AI ultimately. It is really important for the system to explain to the user why it is resulting out a particular decision and also ask the analyst for clarification for a better outcome. This is not simply a trend that comes and goes away, the ultimate purpose of using intelligent systems and tools is not to replace human expertise but to assist them collaboratively. AI has to be trusted to make a powerful impact in making intelligent decisions for businesses and the reasoning should come from AI itself.

2. Mixing Linguistics with BI tools

Giving more flexibility and conversational power to users of BI tools will change the way the questions will be asked about data. Using the power of analytics and getting insights into data will not be limited to data scientists and analysts but also to a general user who has questions that need to be answered based on data. This aspect of Mixing Linguistic with BI tools is fundamentally a branch of AI that combines linguistics and computer science to make computers understand the emotions and meaning behind the human language. This will enable us to ask follow-up questions based on a context for example, how many times did the hurricane approach Florida? Following up with a question, ”Did it approach Houston too?”.

3. Modern Data Curation Techniques

Data sources have become quite complex and the problems of gathering the data from various sources and then cleaning, defining, and aligning them for analytics is difficult. Organizations have and will be spending hefty amounts of money in tools that govern everything under one platform. Business Intelligence platforms such as tableau, power BI help in linking data with the context of the business.

4. Bringing actions and insights together

People working with data do not want to perform analysis in one environment and take action based on the results in another. BI platforms have taken the charge of merging business workflows and operations via mobile analytics and dashboards. The purpose is to have everything in one view and take actions without having the user to leave the analytics workflow and ultimately reduce time and effort for making decisions.

5. Communicating Data Insights

Data Science is more of an art than science. The last stage of any sort of analysis is reporting, presenting, and communicating the insights. Analysts use different methods to visualize data so that they can convey information to decision-makers in the best possible way. There is a shift in the trend and in the years to come more and more companies will adopt a standard way for analysts to do “storytelling”. As storytelling will make its way in businesses that will adopt data-driven decision making, more people will understand how to explain their analytical process and interpret data.

6. Data Roles will diversify

As of today, data scientists, data engineers, data analysts are very popular job profiles and almost everyone is speaking about the lack of workforce in this sector. As more and more organizations will use data to make business and internal decisions, there will be a boom in the diversity of work profiles in the data industry. Many companies have a separate team of data workers with different responsibilities and the trend will continue in 2020 and beyond.

7. Data Security and Value

We are in the information age and data is like a valuable property for any company. For social media companies, data related to customers is of utmost importance and they cannot compromise a breach in security leading to exposure of users’ personal information to a third party. ML engineers will understand that it is not about how good and powerful the system is or how good the ML algorithm is that creates sophisticated models, they are important but the most important of all is the quality and amount of data a company has. In the future people are going to pay for data because no everyone is going to have access to information like that of Amazon, Google, Facebook, Netflix, and the big techs. A data leak will be considered as similar to a bank robbery.

8. Accessibility and Usage of Business Intelligence

The accessibility of the internet to everyone does not imply that everybody is making the best out of it. People fail to realize the true potential. Similarly, the tactics and tools of BI depend on how people use it to make informed decisions. As organizations are getting smarter about adopting data analytics as part of the core business workflow, creating communities and sessions that empower the best data practices will be vital for their workforce to deal with the competitive market.

9. Migrating data to the cloud

As cloud computing is parallelly rising in popularity with other computational domains, businesses cannot overlook it. With time, no matter how small the company is, they will need data-driven solutions for their business and data will be moving to the cloud. Existing systems have a rigid analytical model and many companies rely on their IT departments for analytics which separates the process from the context of their business. The Cloud is not limited to just storage but also have the full-fledged BI tools. The trade-off here would be trusting the third-party cloud server for data security with the amount of money they would need to invest for their own cloud-like service.

10. Ethical Interpretation of Data

We cannot always trust the results of particular data. We have to digest the fact that data can be biased. As more people will be a part of the data industry, ethics will be an integral part of approaching data in certain contexts. In the years to come, we will have guidelines for company-wide data practices because one misinterpreted data result would cause disaster for businesses solely depending on data-driven decisions. Therefore, a helping hand from AI domains and a critical code of conduct for “ethical interpretation” would be extremely vital.

Future technologies are being designed to empower people. Data-based approach help businesses understand the past, present, and future of customer needs. Today search engines have empowered people by giving them a powerful way of finding what they want, social media have empowered them by giving them the tool to connect with whoever they want. Similarly, data-based decisions will empower the businesses and their customers eventually. Business Intelligence tools can harness the past, present, and future of consumer behavior and this will definitely have an impact on providing quality services and experience to everybody.

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