Since its early inception in the 1990s, business intelligence (or as commonly referred BI) has evolved from a technical and IT-centric process to a more inclusive and IT-enabled process in the last decade. So, how are BI and data analytics poised to evolve in the 2020 decade?

As data analysts, we are witnessing the convergence of various other technologies including cloud platforms, artificial intelligence and machine learning, business analytics, and the powerful Internet-of-Things (IoT) all of which are set to transform the capabilities of future technology. Have a look at how Artificial Intelligence is transforming business analytics and business intelligence

business intelligence 2020

Additionally, data-centric companies are adopting both BI and analytics to make sense of the growing volumes of business data. Among the leading business intelligence trends in 2020, the BI job market is estimated to grow up to over 2.72 million jobs (in the data science field) by the end of 2020. According to Forbes, business dashboards, BI reporting, and self-service BI are the three most popular use cases for organizations deploying BI tools.

Next, we shall look at some of the leading industries that are using business intelligence along with the 10 leading business intelligence trends in 2020 across the globe.

5 Leading Industries That Rely On Business Intelligence

Business Intelligence is no longer just a buzzword used in technology companies. It is being used by a variety of industry domains to gain a competitive advantage in the respective marketplace. Here are 5 of the leading global industries that are benefiting the most from BI adoption:

Retail industry

Be it the brick-and-mortar store or online eCommerce, loss of valuable inventory is a consistent problem. Thanks to BI and data warehousing solutions, retail companies can keep a closer look at their inventory stocks and reduce their business losses.

Food processing industry

Environmental sustainability is today’s topmost priority for any business in food retail or processing. This includes the mass-scale use of healthier and safer ingredients, environment-friendly food packaging, and eco-friendly distribution mediums.

Business intelligence is enabling the food industry to identify or develop sustainable methods through eco-friendly technologies. Through BI-powered data collection tools, food companies are more sensitive to environmentally sustainable demands.

Pharmaceutical industry

Among the major issues facing the global pharmaceutical industry include the lack of non-compliance to health regulations due to the distribution of expired medicines along with managing product patents. BI tools enable pharma companies to minimize the distribution of products (with expired dates). Additionally, this technology is transforming traditional patent laws and improving the rate of development in new drugs.

Oil & Gas industry

BI and other associated technologies can derive insights from geological data to determine the location of oil and gas deposits. Thanks to data-driven technology, the oil & gas industry are able to keep control over oil & gas prices as well as increase their profitability.

Fashion industry

Among the widely competitive industry globally, the fashion industry relies heavily on BI and other data-powered technologies to determine customer needs and gain a competitive edge. Thanks to valuable insights driven by BI, fashion companies can target the right fashion clothing to its consumers. Additionally, fashion companies can determine global trends in the fashion industry and come up with the right business goals.

Now that we have the major global industries that are relying on BI for business success, let’s next look at the top 10 business intelligence trends in 2020 that are impacting these industries.

10 Leading Business Intelligence Trends in 2020

Let’s get started with the 10 leading trends in BI.

Data Quality Management (or DQM)

Data quality continues to be among the major challenges facing data analysts around the globe. Good data quality is critical for deriving the right insights from the available data and taking the right decisions.

Data quality can be measured based on the following parameters:

  • Completeness: Is the available data complete or are there any missing values?
  • Validity: Does the available data match up to the prescribed rules?
  • Uniqueness: Does the data contain any duplicate entries?
  • Consistency: Are you accessing consistent data across multiple data sources?
  • Timeliness: Is the available data updated to the latest records?
  • Accuracy: How accurate or real is the generated data?
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Among the most promising trends in BI, Data Quality Management (or DQM) is crucial for avoiding the pitfalls for poor data quality and leveraging any company’s investments in BI technologies. DQM-related processes ensure that the business acquires compliance with data quality standards and regulations across the globe.

Business Intelligence for Sales and Marketing

Another leading trend is the use of business intelligence for sales and marketing teams across companies. Thanks to the use of BI dashboards, sales, and marketing professionals can access the latest sales and purchasing trends among their customers without relying on any technical IT expert or business analyst.

How do BI tools improve the returns from any sales or marketing activity? Here are a few pointers:

  • Improve the accuracy of sales targets and forecasts.
  • Measure the market impact of the latest marketing campaign or promotion.
  • Devise business strategies for acquiring new and retaining existing customers.
  • Identify and focus on the most valuable customers that are generating the most profits.
  • Prepare the right marketing message for individual customers based on the value and frequency of their purchases.
business intelligence for sales and marketing

Through the adoption of the right business intelligence tools for sales and marketing, companies can benefit from higher revenues (due to product cross-selling and up-selling) and ensure higher customer satisfaction.

Data Discovery

Also referred to as data analysis for business users, data discovery is among the leading business intelligence trends in 2020. For a business user, data discovery is a business process aimed to detect patterns and deriving insights in data through data analytics tools. 

data discovery in business intelligence

As a business process, data discovery comprises of the following three stages:

  1. Data preparation stage where business users are connected to multiple data sources.
  2. Data visualization stage where business users can easily perform visual data analysis using data visualization dashboards containing informative charts and graphs.
  3. Data analytics stage where business users can use analytical skills to identify advanced patterns in the available data.

Thanks to the visualization tools, business users are able to discover business trends and even anomalies easier and take immediate and appropriate actions.

AI and Machine Learning in Business Intelligence

Be it through chatbots or data-driven personalized services, 97% of industry experts see a major role for technologies like artificial intelligence and machine learning in marketing. At the same time, AI and machine learning can also be deployed in business strategies related to business intelligence and analytics.

Artificial Intelligence and Machine Learning in business intelligence

Among the latest trends identified in the 2020 Gartner report, AI and machine learning technologies are useful for detecting any anomalies or unexpected patterns in data analytics. For example, through advanced neural systems, AI algorithms can analyze historical data and accurately detect anomalies or unexpected events.

Predictive Analytics & Reporting

Be it for determining customer value or make sales forecasts, predictive analytics and reporting is among the popular trends in business intelligence. With the availability of big data for data analytics, Bi tools possess the capabilities of determining future business trends from the current data patterns.

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Global industries are combining predictive analytics and BI for a number of use cases. For example, airline companies can use these technologies to estimate customer demands and determine an optimum ticket price. Similarly, banks and financial institutions can use these insights to calculate the credit score of any customer.

Collaborative BI

In simple language, collaborative business intelligence is the collaboration between BI technology and online collaboration tools like social media and web technologies.

With the emergence of faster data collection and analysis, collaborative BI is an industry trend associated with a faster decision-making process. Collaborative BI enables seamless sharing of BI reports along with enhanced interactivity among business users.

collaborative business intelligence

Aimed towards better problem-solving solutions, collaborative BI tools enable exchange of business ideas or problem solutions through Web 2.0 tools such as Wiki and blogging.

Augmented Analytics

According to a Gartner study, augmented analytics is the leading trend in business intelligence in the year 2020. Additionally, the global market for augmented analytics is expected to reach a value of $13 billion by the year 2023. Powered by technologies like AI and machine learning, augmented analytics tools enable even average users to build complex data analytics models and easily derive deeper insights from them.

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As an industry use case, augmented analytics in the eCommerce industry enables online retailers to use multi-channel marketing to promote and sell their products across multiple channels.

Self-Service BI

Traditional BI tools are structured around a central data warehouse and data stores. However, this centralized infrastructure is insufficient for today’s business enterprise that needs to have data access anytime and by any user. 

This has led to the emergence of the self-service BI model that provides BI users with more flexibility and independence when it comes to accessing data.

self service business intelligence

Based on user roles and responsibilities, self-service BI categorizes users as follows:

  • Business analysts that comprise of around 1-5% of all BI users.
  • Power users that comprise around 25% of all BI users and require more flexibility for working with business data.
  • Casual users who have limited BI-related skills and make up to 70% of all BI users.

Data Automation

Also referred to as hyper-automation, data automation is rated among the most disruptive technologies for the year 2020. Gartner predicts that 40% of all data science-related tasks will be automated by this year, thus making data automation a BI trend to watch out for this year. 

data automation in business intelligence

The variety of available data sources that businesses use is still a major bottleneck for businesses trying to consolidate and analyze all the generated data. Data automation solutions in BI aims for data consolidation that enables analysts to collect and analyse large data volumes.

Embedded Analytics 

When it comes to embedded analytics and BI, this latest BI trend is being adopted by various data-centric businesses. According to Allied Market Research, the global market for embedded analytics is expected to reach $60 billion by the year 2023.

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By integrating BI solutions such as BI reports or dashboards within native applications, embedded analytics enables business users to analyze data faster and make decisions without having to switch to another software tool.


The success of business intelligence and analytics can be easily gauged by its growing adoption among various industry domains as highlighted in this article. This article also presented an overview of the 10 top business intelligence trends in 2020 and for the next decade.

With customized solutions in business intelligence and analytics, Countants is providing a competitive advantage that is enabling its global clients to thrive and succeed. The company is providing cloud-based solutions with the latest cutting-edge technology that is designed for customer success.

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