The global Business Intelligence and Analytics market this year has already reached or is nearing $16.9 Billion, according to Gartner. The BI and Analytics market has undergone a major transformation from an enterprise IT-led, record reporting system to business-driven self-service data explorations. This turnaround of trends in Business Intelligence (BI) and Analytics indicates a larger trend of mainstreaming or democratizing all data technologies. The need for “accessibility, agility and deeper analytical insights” has never been more intensely felt in businesses before.
In the current business scenario demanding immediate time-to-insight, it is no longer sufficient for the CMOs to have expertise in branding or ad placement, they are also expected to be experts on customer analytics. The current Business Intelligence and Analytics trends can be broadly categorized into three categories, trends that are common to BI and Advanced Analytics, Bi-specific trends, and Analytics-specific trends.
In the context of this article, the reader needs to understand how BI has been differentiated from Advanced Analytics. For the discussion of this article BI has been viewed as a explorative data platform with a set of in-built tools that extracts meaning or insights from many types of data like historical (static), real-time (dynamic), and mix use. On the other hand, Analytics enables drilling (drill up, down, lateral) of available data for specific, need-based business outcome such as predictive models.
Given the above context, now it is time to look at operative market trends in today’s Business Intelligence and Analytics applications.
Common Data Trends
The following trends encompass all data-related activities, especially Business Intelligence and Analytics.
Self-service Data Explorations
While traditional dashboard BI is receding into the background, self-service machine Data Analytics, self-service data discovery and explorations, BI and Analytics on the Cloud are rapidly gaining momentum across the global spectrum.
Business Intelligence and Analytics with Big Data
With technologies like Hadoop, the Internet of Things, and Machine Learning aiding modern Analytics, the entire BI and Analytics focus has shifted to the business corridors from the closed door chambers of data centers.
IT to Shift Business
Today’s BI and Analytics consumers are closer to the technological hotbeds. Thus corporate leaders, operators, and staff are newly empowered by real-time, business insights flashing on their laptop or mobile displays. Gartner feels that as Analytics is becoming a core function of every business role, virtually every business process is turning into an Analytics process, and every business staff in converting into a Data Analyst.
Cloud as Mainstream
The small to mid-sized businesses with limited financial horsepower have all invested in Cloud-based BI-as-a-Service or Analytics-as-a-Service platforms. Thus, they are uniquely positioned to access powerful business insights on the fly, which was not possible even five years ago. This Business Intelligence and Analytics trend is a powerful game changer, especially for small to mid-sized businesses.
The DATAVERSITY® article 2016 Trends in Business Intelligence and Data Analysis describes some of the Cloud offerings that companies like Dirking and Aletryx are using to enhance their data technology capabilities.
Mixed Data Mashups
According to a CIO last year there were 21 Data and Analytics Trends that Will Dominate 2016, many of these are still being realized and will see impacts far into the future. The combined force of social, mobile, and Cloud technologies has caused a major disruption in data handling techniques used in today’s BI and Analytics applications. Data Mashup is a new and novel concept gaining wide popularity across global enterprises. Tech Target’s Data Mashup Tools Boost Business Intelligence and Analytics Efforts indicates that currently data discovery tools are allowing businesses to extract data from multiple systems, both internal and external. Also, some BI applications enable data pull in through point-and-click interfaces. Lastly, data islands are developing that combine data from “enterprise data warehouses and big external sources such as web logs, industry hubs, social media, and sensors.”
The Democratization of Data Access
Thanks to solutions like Amazon Mechanical Turk, now small, medium, or large businesses can locate, acquire, and explore data from around the world without too much technology savvy. This is probably the most important Business Intelligence and Analytics trend ready to set the stage for next generation data technologies.
Increased Concerns about Data Privacy
As data become accessible and sharable on a global platform, the growing concern about data privacy will remain reality. Europe has set forth regulations around enterprise data security, which necessitates pre-planned Data Governance with full compliance to global and local laws, rather than an afterthought activity.
Business Intelligence Specific Trends
Self-Service Business Intelligence
The systems with embedded BI and rule engines are increasingly becoming popular among CIOs and managers, who can get their daily work done without any IT involvement. More and more, IoT data will become mainstream in business processes, necessitating the use of Machine Learning enabled BI among business staff.
Use of Data Mashups in Business Intelligence
Data Mashup Tools Boost Business Intelligence and Analytics Efforts suggests currently, data discovery tools are allowing businesses to extract and combine data from multiple systems for enhanced Business Intelligence. Many of these applications are Cloud based, and support diverse data formats across systems through simple point-and-click interfaces. Enterprise data islands leverage data integrated from data warehouses and other external sources such as social media, web logs, and IoT devices.
Geospatial BI for Competitive Edge
The introduction of specialized geospatial technologies and tools have further strengthened the power of Self-Service Business Intelligence. With location-centric BI, businesses are better positioned to explore new markets, target micro markets, or position products for specific markets.
Data Science has Invaded BI
Use of Big Data and real-time machine data are the primary features of current hosted BI systems, which combine many technologies to deliver real-time market intelligence.
Analytics Specific Trends
Self-Service Analytics
This type of Analytics is pursued by line-of-business professionals with the least amount of IT involvement. The Analytics activities are characterized by simple point and click BI applications with in-built Advanced Analytics tools. Most of these Analytics tools have underlying data models simplified or scaled down for ease of data access.
Focus on Location Analytics
DATAVERSITY’s 2016 Trends in Business Intelligence and Data Analysis states that the introduction of advanced geospatial tools in Analytics has provided global businesses a competitive edge. This edge is primed to continue its importance and growth moving forward.
Emphasis on Visualization
KDNugget’s Gartner’s Magic Quadrant Analytics Platforms Gainers and Losers indicates that SAS Analytics, known for its leadership role in the Analytics market, has significant improvements in its Visual Analytics and Visual Statistics products with user-friendly interfaces to encourage citizen Data Scientists to pursue data analysis. When a company like SAS champions a new Analytics trend, it is surely to be followed by other Analytics vendors. Market studies indicate that while traditional BI tools are not witnessing any growth, data visualization and data discovery tools are growing in double digits.
Continuous Intelligence on the Cloud
This year has seen a major growth of hosted Analytics platforms. Analytics-as-a-Service, mainly on the Cloud, is a reality that will remain in future. Even large businesses are moving away from on-premise BI and Analytics setups to continuous intelligence in real time.
Log-Data Analytics
By harnessing the insights inherent in real-time log Data Analytics, companies will have faster access to operational and customer data that can enable 24/7 innovation and sustain their competitive edge. Today, businesses need Analytics tools to continuously monitor, manage, and acquire intelligence from user, process, or system logs for gaining a competitive edge.
More Machine Data Analytics
Though Machine Data Analytics is in its infancy, the maturation of Big Data technology has catapulted the Machine Analytics market to a CAGR greater than 1000. As the need for “speed, full-stack visibility, and agility in real-time” grows, the advancement of Machine Data Analytics is inevitable.
Also read Data Analytics Trends to Watch in 2016 from Venture Beat to understand how the projected Business Intelligence and Analytics trends have unfolded this past year and will affect the Business Intelligence and Analytics market trends through 2017 and beyond.