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Business Intelligence and Analytics Trends in 2018

By   /  December 7, 2017  /  No Comments

Business Intelligence and Analytics Trends Thanks to the rapid growth of Machine Learning (ML) and Deep Learning (DL) in the recent years, the Business Intelligence and Analytics trends in 2018 are filled with considerable change. The deep penetration of the Internet of Things (IoT) and Big Data in the global business environment has naturally sparked the need for smart Business Intelligence (BI) systems, which can to a large degree, automate decision making, thus removing the need for data professionals.

If the current BI systems used in financial services, investment banking, market research, or even healthcare industries are standards to go by, then Smart Data Discovery, powered by Machine Learning is the next game changer for businesses of all sizes and shapes.

According to Gartner, the Business Intelligence market is expected to grow to US$22.8 Billion by 2020. So, what do these game-changing Business Intelligence and Analytics trends offer to the businesses? Certainly, better visualization coupled with deep data drilling capabilities. Although the BI systems are getting increasingly sophisticated and more complex in terms of technology, here are some transformative trends that have been predicted for 2018.

Market Size and Technology Scope

According to a statistics-heavy Report from Business Intelligence, Business Intelligence Market Expected To Grow $20.81 Billion By 2018, the sudden growth of the 2018 BI & Analytics market will encompass traditional BI, hosted (Cloud) BI, social BI, and mobile BI. The entire market will touch down on $20.8 billion in 2018, which translates to “an estimated CAGR of 8.3% from 2013 to 2018.”

The Forbes blog post titled Top 10 Trends For Digital Transformation In 2018  suggests that IoT enabled Business Analytics has the power to maximize operational efficiency in every industry sector from “retail to city planning.” The technology torch-bearers like IBM or SAP are investing more on Business Analytics capabilities, now that IoT and Big Data promise to deliver on streaming, operational, and transactional data in real time. Another example of a universal technology is the Blockchain, which began in the financial services but has gradually found its way into hospitality, healthcare, and some other industry sectors. By 2020, according to Datamation, only 20 percent of trade finance will utilize Blockchain, but once the trend is well set, there will be no looking back.

The Rise and Growth of Data Analytics

The sudden prominence of Data Analytics in the global business community has been triggered by the volume and variety of business data, which creates unique challenges for BI and Analytics users. The article titled Disruption Ahead: The Big Trends In Business Intelligence Analytics by the Digitalist magazine claims that the transformative BI will not only increase user adoption, but also promote the utilization of BI platforms among mainstream business users. Also read The Top 10 Technology Trends for 2018 to understand how AI, Cloud, IoT, and business apps will jointly contribute to reshaping the IT landscape in every business.

Top Tech Trends of 2018 BI & Analytics Market

The industry-wide buzz is that given the criticality of immediate and accurate decision making, every business user wants to have the capability for independently visualizing and analyzing data for improved results. According to the blog post titled Top Business Intelligence Trends to Watch Out for This 2018, the hallmarks of ‘modern’ BI are enhanced Data Visualization, deep Data Mining, and intelligent Self-Service Analytics.

The author of this Dataviz article claims in Top 10 Strategic Technology Trends for 2018 that Gartner’s Technology Trend No. 2, which is Intelligent Apps and Analytics will ensure that in the next few years, every business application or service embraces AI at some level. This article further states that the market fetish for “everything AI” is giving rise to a battleground for all analytics platforms and service providers.

Forrester Wave Reports on BI platforms have traditionally segmented the advanced visualization tools from the low-end reporting and regular visualization platforms. According to The Forrester Wave™: Enterprise BI Platforms with Majority On-Premises Deployments, Q3 2017, enterprise BI platforms, which featured advanced Business Intelligence capabilities required data professionals to develop the output. The mainstream BI platforms like Tableau and Qlik, on the other end satisfied the needs of ordinary business users. However, now Forrester acknowledges that advanced visualization is integral to most BI platforms, especially because Cloud-based BI has made it possible for medium or small sized businesses to have access to advanced analytics. Many of the features that differentiated scalable systems from low-end systems before are now commonly found across BI platforms.

The changing landscape within the overarching heading of Business Intelligence and Analytics trends have given rise to two major challenges that have to be mitigated by businesses of all sizes to democratize BI and extract real value from analytics activities.

Challenge 1: Managing Large Troves of Business Data

As global businesses gear up to utilize the novel smart data discovery and Augmented Analytics platforms in 2018, the most difficult problem is always the massive volumes of data. In traditional BI & Analytics systems, 80 percent of this data remained unused or underutilized, thereby severely restricting the usefulness of the analytics systems. Now with hosted BI platforms and IoT devices pouring out diverse types of data, advanced data cataloging tools are required to access data from many different sources. Read the ZDNet article titled Data to Decisions: New Trends in Leveraging Analytics, to understand how the businesses have planned to face the data volume challenge.


Challenge 2: Limitations of ML-Powered Predictive Models

According to the The Forrester Wave™: Predictive Analytics and Machine Learning Solutions, Q1 2017, Data Scientists in 2017 required tools to develop ML-powered, predictive models, and a platform to manage the models. Though these BI platforms gained popularity among the data professionals, no one ever thought that these tools had the potential to replace the human Data Scientists, and make way for Self-Service BI. That said, as businesses continue to depend on Self-Service BI & Analytics enabled by Big Data, Cloud, IoT, and Predictive Analytics tools for all types of decision-making, Self-Service Analytics platforms with superior data visualization capabilities will gain momentum in 2018.

According to the blog post titled What Does Business Intelligence Look Like in 2018?, organizations are slated to embrace the “self-service” BI, but of course with more governance, so that business users have more control over the data they analyze.

Augmented Data Preparation and Augmented Analytics

Both Augmented Data Preparation and Augmented Analytics are designed to empower the citizen Data Scientist with tools that go beyond data discovery, and helps prepare business data in a manner which facilitates “strategic, operational and tactical activities” for future business planning. With Augmented Data Preparation, common business users will be able to test the data against particular hypotheses without the help of IT staff. On the other hand, Augmented Analytics will deliver insights through advanced ML-enabled tools. The ultimate goals of these two novel technologies are to rapidly increase user adoption and enhance data awareness. Get the full story in DATAVERSITY®’s What is Augmented Analytics and Why Does it Matter?

Business Analytics Landscape in 2018: The Top Trends
Given the two major challenges just described for the future generation of BI and analytics, here is a round-up 2018 Business Intelligence and Analytics trends, as confirmed by reliable industry literature:

  • Augmented Data Preparation will gain popularity among the business users as they will be able to pursue data-testing tasks without the help of IT staff.
  • Data visualization, which emerged as the front runner of 2017 trends, will continue to dominate the BI platforms in 2018.
  • Smart Data Discovery will give a tremendous impetus to predictive analytics in 2018, making it the favorite business analytics activity.
  • With the passion for going “visual,” citizen Data Scientists or mainstream business users will depend on mobile analytics in 2018 for day-to-day decision making. Augmented analytics will be a sought-after capability for mainstream BI users.
  • The larger organizations will heavily invest in building an in-house BI/analytics platform.

The blog post titled Business Intelligence (BI) Trends to look forward to in 2018 describes these impending trends very well. In DATAVERSITY®’s To Get Value from Data, Data Discovery Must Come First!, the readers of this post will get a sense of the advanced statistical tools and ML capabilities of modern BI systems, which carry the promise of innovative analytical solutions. This has been possible due to the increased data awareness through superior data visualization and data understanding.

While traditional BI technologies have been lacking in good data storage facilities or good data visualization tools, the modern ML-powered analytics platforms bring improved data visibility and comprehension. The new data discovery methods promise huge cost reductions and enhanced results.

 

Photo Credit: ra2studio/Shutterstock.com

About the author

Paramita Ghosh has over two and a half decades of business writing experience, much of which has been writing for technology and business domains. She has written extensively for a broad range of industries, including but not limited to data management and data technologies. Paramita has also contributed to blended learning projects. She received her M.A. degree in English Literature in 1984 from Jadavpur University in India, and embarked on her career in the United States in 1989 after completing professional coursework. Having ghostwritten and authored hundreds of articles, blog posts, white papers, case studies, marketing content, and learning modules, Paramita has included authorship of one or two books on the business of business writing as part of her post-retirement projects. She thinks her professional strength is “lifelong learning.”

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