Technologies In Use To Support BI Analytics

The top technologies In use to support BI and Analytics:

Data warehouse or mart in the cloud (41%)

Data lake in the cloud (39%)

BI platform in the cloud (38%)

Cloud data storage (object, file, or block) and data virtualization or federation (both 32%) are the next-most planned for technologies by enterprises when it comes to investing in the analytics and BI initiatives

Source: TDWI

BI & Analytics Investment Priorities

82% of enterprises are prioritizing analytics and BI applications and platforms as part of their budgets for new technologies and cloud-based services

78% of enterprises are prioritizing advanced analytics

76% data preparation

54% say AI, machine learning and Natural Language Processing (NLP) are also a high investment priority

Source: TDWI

The Importance of BI Cloud Computing

An all-time high 48% of organizations say cloud BI is either “critical” or “very important” to their operations in 2019.

Organizations have more confidence in cloud BI than ever before, according to the study’s results. 2019 is seeing a sharp upturn in cloud BI’s importance, driven by the trust and credibility organizations have for accessing, analyzing and storing sensitive company data on cloud platforms running BI applications.

Source: Dresner Advisory

The Importance Of Cloud BI Computing By Function

Marketing & Sales place the greatest importance on cloud BI in 2019.

Business Intelligence Competency Centers (BICC) and IT departments have an above-average interest in cloud BI as well, with their combined critical and very important scores being over 50%.

Dresner’s research team found that Operations had the greatest duality of scores, with critical and not important being reported at comparable levels for this functional area.

Dresner’s analysis indicates Operations departments often rely on cloud BI to benchmark and improve existing processes while re-engineering legacy process areas.

Source: Dresner Advisory

The Importance Of Cloud BI Computing By Organizational Size

Small organizations of 100 employees or less are the most enthusiastic, perennial adopters and supporters of cloud BI.

As has been the case in previous years’ studies, small organizations are leading all others in adopting cloud BI systems and platforms.

Perceived importance declines only slightly in mid-sized organizations (101-1,000 employees) and some large organizations (1,001-5,000 employees), where minimum scores of important offset declines in critical

Source: Dresner Advisory

BI Analytics Tools Customer Satisfaction

The 3 most important factors in delivering a positive user experience include:

Good query performance (61%)

Creating and editing visualizations (60%)

Personalizing dashboards and reports (also 60%)

The three activities that lead to the least amount of satisfaction are:

Using predictive analytics and forecasting tools (27% dissatisfied)

“What if” analysis and deriving new data (25%)

Searching across data and reports (24%)

Source: TDWI

Augment or Replace Existing BI Analytics Data Warehousing Systems

82% of enterprises are looking to broaden the base of analytics and BI platforms

18% of enterprises plan to add more instances of existing platforms and systems

The top three system areas enterprises are planning to augment or replace existing BI, analytics, and data warehousing systems:

Cloud-native platforms (38%)

A new analytics platform (35%)

Cloud-based data lakes (31%)

Source: TDWI

The Importance Of Cloud BI Computing By Industry

R&D departments are the most prolific users of cloud BI systems today, followed by Marketing & Sales.

he study highlights that R&D leading all other departments in existing cloud BI use reflects broader potential use cases being evaluated in 2019. Marketing & Sales is the next most prolific department using cloud BI systems.

Source: Dresner Advisory

Plans to Use Cloud BI Computing By Cloud Model

Finance leads all others in their adoption of private cloud BI platforms, rivaling IT in their lack of adoption for public clouds.

R&D departments are the next most likely to be relying on private clouds currently. Marketing and Sales are the most likely to take a balanced approach to private and public cloud adoption, equally adopting private and public cloud BI.

Source: Dresner Advisory

Importance of Cloud BI Computing Features

Advanced visualization, support for ad-hoc queries, personalized dashboards, and data integration/data quality tools/ETL tools are the four most popular cloud BI requirements in 2019.

Dresner’s research team found the lowest-ranked cloud BI feature priorities in 2019 are social media analysis, complex event processing, big data, text analytics, and natural language analytics.

This years’ analysis of most and least popular cloud BI requirements closely mirror traditional BI feature requirements.

Source: Dresner Advisory

Magic Quadrant for Analytics and Business Intelligence Platforms

Source: Gartner

Go to Market BI Research – IDG’s CIO Tech Poll – BI Spending

When respondents to CIO’s Tech Poll were asked if their spending for each of the following applications / operating platforms increase, decrease or remain the same next year, compared the the previous 12 months, 70% stated that they expected an increase.

Go to Market BI Research –Gartner Predicts – Business Intelligence

• Gartner predicts that by 2017, virtually all new analytic software purchases will begin as a free or low-cost proof of concept, enabling buyers to try the software before they buy.
• Gartner predicts that by 2018, most of the stand-alone self-service data preparation vendor offerings either will have expanded into end-to-end analytical platforms, or will have been integrated as features of existing analytics platforms.
• Gartner predicts that by 2018, smart, governed, Hadoop-based, search-based and visual-based data discovery will converge into a single set of next-generation data discovery capabilities as components of a modern BI and analytics platform.
• Gartner predicts that by 2019, 80% of new applications using IoT or machine data will analyze data in motion as well as collect this information for analysis of data at rest.

Source: MemSQL

Go to Market BI Research –Gartner’s 2016 BI Magic Quadrant

Gartner released the 2016 version of their Magic Quadrant for Business Intelligence and Analytics Platforms. According to Gartner, the enterprise business intelligence industry has crossed the chasm and is completing its evolution from a market based heavily on reporting tools to one that is more business-centric, user friendly, offering self-service analytics to facilitate a plethora of users to get their hands on tools that drive insights. The majority of BI purchases now comes in the form of modern platforms that center on user engagement and that is what is driving changes to the vendor landscape and the magic quadrant.

Based on the changes in the market (the shift in buying decisions from IT to business stakeholders), Gartner has changed their paradigm to assess vendor performance in the Bi space.  Centralized provisioning and tightly governed platforms are becoming a thing of the past.  Tools that promote analytical agility and business user autonomy is what users are asking for and what vendors are delivering.  In response, Gartner has adapted its approach and the 2016 Magic Quadrant is based on platforms with modern capabilities.

Gartner’s BI & Analytics report is now based on the following five main use cases:

• Agile Centralized BI Provisioning
• Decentralized Analytics
• Governed Data Discovery
• Embedded BI
• Extranet Deployment

Go to Market BI Research – Gartner Predicts Global Business Intelligence and Analytics Market to Reach $16.9B in 2016

The Gartner forecast for business intelligence (BI) and analytics is that the market will reach $16.9B in 2016.  That represents over a 5% increase from 2015.

Gartner analysts believe that the BI and analytics market near the final stages of a shift from IT-led, system-of-record reporting to business-led, self-service analytics–a change that has been anticipated by Gartner. The benefit to organizations is a modern business intelligence and analytics (BI&A) platform that enables accessibility, agility and deeper analytical insight.

Garter includes a high-level comparison of traditional and modern BI and Analytics platforms broken down by three segments

• Analytics workflow components
• IT-centric reporting and analysis platform
• Modern BI and analytics platform

Analytics workflow components include data source, data ingestion and preparation, content authoring, analysis and insight delivery.

Go to Market BI Research – IDC Worldwide Business Analytics Software Market Shares

IDC continues to produce detailed supply-side quantitative metrics for markets and vendors that are detailed and pragmatic.  The IDC report,Worldwide Business Analytics Software Market Shares, 2015: Healthy Demand Despite Currency Exchange Rate Headwinds, should be something every B2B marketing team is familiar with and leverages in their go to market plans.

IDC defines the business analytics software market to include horizontal tools and prepackaged analytic applications that include:

• Software to support the full life cycle of data integration
• Integrity
• Analysis
• Visualization
• Related decision support functionality

Go to Market BI Research – IDC Key Takeaways

• In 2015, the global business analytics software market grew 2.5%
• Growth rates varied among the 12 market segments
• The fastest-growing markets were content analytics, customer relationship analytic applications, and advanced and predictive analytics.
• The two largest market segments, end-user query, reporting, and analysis and analytic data management grew slowly (0.7% and 2.7%, respectively).
• 2015 was the beginning of the migration to the cloud.
• The on-premises portion of the overall market contracted by 1.4%
• Public cloud services revenue grew 26.5%.
• Public cloud portion of the market now represents 17% of the overall market.
• Cloud adoption of analytic applications: 40%
• Cloud adoption of the aggregated category of business intelligence (BI)/analytics tools, analytic data management and integration platform, and spatial information analytics tools: 7%

Go to Market BI Research – Market Share – Global Business Analytics Software Revenue

• Oracle $6.8B, 16.4% share, -2.8% growth
• SAP $5.4B, 13.1%, -6.2%
• IBM $4.3B, 10.3%, -7.2%
• Microsoft $3.8B, 9.1%, 10.4%
• SAS $2.9B, 6.9%, 4%
• Teradata $1B, 2.5%, -7.8%

Go to Market BI Research – Market Share – Global Business Intelligence & Analytics Tools Software Revenue

• SAP $2B in revenue, 14.4% share, -12.6% growth
• Microsoft $1.5B, 10.7%, 9.7%
• SAS , $1.4B, 9.9%, 6%
• IBM $1.4B, 9.8%, -10.2%
• Oracle $1B, 7.4%, -2%
• Tableau $.6B, 4.5%, 57.9%

Go to Market BI Research – Global Analytics & Business Intelligence Applications

In 2015, the Global Analytics and Business Intelligence applications market grew 4% to approximately $11.6B in license, maintenance and subscription revenues

• SAP had a 10% market share with $1.2B in Analytics and Business Intelligence (BI) product revenues – this was a23% jump in license, maintenance, and subscription revenues.
• SAS Institute was second with a 9% market share
• IBM was the third with an 8% share
• Oracle and Microsoft followed with a 7% and 5%, respectively

The worldwide analytics and BI applications market is forecast to reach $13.7B in 2020 – 3.3% CAGR

NOTE: Analytics applications cover business intelligence functions sold as a standalone application package for decision support or embedded in an integrated solution for functions such as revenue performance or for specific verticals such as healthcare performance management

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