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A Comparative Roundup of Business Intelligence and Analytics Trends: Product Development

By   /  March 2, 2017  /  No Comments

Gartner has predicted that the current size of the global Business Intelligence and Analytics market is upwards of $16+ billion. The product development trends in this combined market have maintained the tempo of Self-Service Business Intelligence (SSBI) and guided data discovery with limited intervention from IT. The emerging need for “accessibility, agility and deeper analytical insights” has forced Business Intelligence (BI) vendors to adapt their system to more mainstream use.  The singular focus of BI or Analytics platforms in 2016 had been to democratize data technologies to accommodate more businesses in the mainstream Data Science community. With that focus in mind, this article explores the biggest Business Intelligence and Analytics trends in terms of product development. The common trends will be explained first, followed by contrasting trends in the two separate categories.

This article treats a traditional BI system as a data exploration platform with pre-built tools for deriving market intelligence or insights from diverse data, while an Advanced Analytics platform as a set of tools for drilling available data for specific business outcomes such as predicting churn or locating micro markets.

The Primary Business Intelligence and Analytics Trends

The product development trends described in this section encompass all BI an Advanced Data Analytics platforms:

  • Prebuilt Reporting Functions: To make Data Analytics and BI functions easy to use and understand, solution vendors like SAP, Oracle, Microstrategy, and Tibco offer report templates to assist the reporting of business processes. While IBM or SAP depends on external BI tools for comprehensive BI-analytics; Information Builder, Tibco, and Microstrategy solutions offer enterprise operational reporting across disparate systems at an affordable price.
  • Data Discovery Functions: The trend has been toward assisted data exploration from solution vendors like Tableau, Spotfire, or Tibco. These BI platforms have segregated the routine Data Management tasks from Data Analytics. The Data Management tools are targeted to enterprise IT departments to source ad integrated business data and ensure data privacy and security. The top-end Business Intelligence tools are targeted to ordinary business users, which includes a host of graphics, reporting, and dashboard tools. This product development approach is a conscious move toward Self-Service BI, where business users can solely focus on data exploration and analytics laving the back-end data management tasks to IT.
  • Packaged BI Solutions: Enterprise BI suites from Oracle, IBM, SAS or SAP offer prebuilt analytics templates and domain-specific tools to aid ordinary business users extract process or performance insights with minimal efforts. For example, the ERP BI modules offered by SAP or Oracle include analytics or operational reporting capabilities specific to ERP systems.
  • On-Premise vs Hosted Platforms: As Software-as-a-Service continues to gain prominence among mid-sized or smaller businesses, more technologies like Cloud Computing, Hadoop, MapR, Big Data will deliver combined BI/Analytics platforms that are hosted on a service provider’s system. This method of mass distribution of Analytics and BI services encourage more businesses, regardless of size and financial horsepower, to reap the business benefits of advanced data technologies. This Business Intelligence and Analytics trends is a move toward the democratization of data technologies.
  • Support for Excel Spreadsheets: Now Microsoft’s flagship product, Excel has in-built capabilities. Power Pivot, Power Query, Power View, and Power Reporting now offer excellent data reporting, visualization, and dashboard features that will enable other BI suites like SAP, IBM, or Oracle use Excel spreadsheets to extract data for further analysis.
  • Query and Ad-hoc Analysis: Both ad-hoc with limited analysis provided by QlikView or Logi Info, and predefined data models provided by SAS, IBM, or Oracle have gained momentum in this year’s product development efforts. Vendors like MicroStrategy and Tableau offer additional functions such as context-based filters, collaboration, and publishing analysis for other types of business operations.
  • Data Visualization Functions: In 2016, BI and Advanced Analytics products have shown a marked preference for analysis-specific visualization tools. SAS Visual Analytics, Qlik Sense and QlikView, or Microsoft PowerPivot all offer advanced data visualization capabilities. TIBCO Spotfire and SAS Visual Analytics also support statistical modeling as part of their visualization tools. The ultimate goal of these vendors is to provide assisted data discovery and guided analysis.
  • Data Preparation Functions: There has been a growing trend toward providing tools for IT departments to build data models with available process or performance measures, which may be supplemented by ordinary business users based on specific needs. The amount of data preparation required for each type of analysis will depend on whether it should be a guided analysis or a SSBI. For guided analysis, QlikView or Microsoft Power BI is sufficient but for more extensive data preparation, Tableau, Qlik Sense, or Logi Vision may be better solutions.

Business Intelligence Product Trends

The BI product offerings in 2017 can be grouped in two broad categories: Solution suites that suit the needs of large enterprises or solutions that suit the needs of smaller enterprises (SMBs).

Business Intelligence Solutions for Large Enterprises
BI solution suites such as Oracle, SAP, Microstartegy, or IBM offer large-scale application development and management features, along with a rich set of Business Intelligence tools that focus on specific use cases. All these solutions provide ad-hoc query, dashboards, data discovery, visualization, reporting, scheduling, notifications, OLAP, varying degrees of Cloud BI, mobile BI, and Self-Service BI. The biggest strength of enterprise-grade BI solutions is that routine Data Management tasks like data privacy, security, scalability, and enhanced performance are all handled by IT to enable business users to concentrate on Data Analytics rather than on data acquisition or data cleansing. The extensive functionality of an enterprise-grade BI suite makes it complex and requires in-depth expertise in products. The large IT-overhead requirements combined with platform expenses make these BI solutions perfect for large enterprises.

BI Solutions for SMBs
The smaller organizations cannot afford dedicated IT teams to manage routine Data Management tasks, so they have taken a different approach for their data technology needs. For medium or small businesses, hosted SaaS services for BI and Analytics may be a better choice. This approach removes the need for maintain on-premise BI infrastructure or dedicated manpower. The business users in these smaller enterprises can access self-service or guided BI and Analytics provided by a hosted service provider like a Cloud BI.

Advanced Analytics Product Trends

Big Data Analytics
The maturation and mainstreaming of Big Data technology has fueled Machine Analytics. With enterprises now relying on Internet of Things (IoT) devices as inputs to Advanced Analytics systems, it is only inevitable that Machine Data Analytics will be integrated in analytics platforms.

Self-Service Analytics
This analytics product trend removes the need for IT professionals in day-to-day Data Analytics tasks. The smart analytics features in enterprise BI systems enable ordinary business users to conduct Advanced Analytics with pre-built data models and simple point-and-click functions.

Increased Focus on Visualization
Many prominent BI platforms like SAS or IBM offers dashboards with visual analytics and statistical modeling functions. 2016 market studies indicate that whereas conventional BI platform have not witnessed any growth in the recent times, data discovery and visualization tools are growing in double digits.

Real-time Analytics
With more connected devices in the future, the Advanced Analytics vendors have been compelled to deliver solutions that “continuously monitor, manage, and acquire intelligence” from business processes in real time for a competitive edge.

Hosted Analytics in the Cloud
2016 witnessed a significant rise in Analytics-as-a-Service platforms, mainly in the Cloud. This trend further removes the need for expensive, on-premise analytics platforms and promotes democratization of data technologies.

Overall, the combined Business Intelligence and Analytics trends moving into the future will demonstrate a preference for self-service platforms and democratization of data technologies, along with further movement into Advanced Analytics solutions that combine various Cloud Computing technologies together.

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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