Business Intelligence Market Intelligence

Industry Outlook & Drivers

Business Intelligence Global Market Outlook:

• The worldwide BI market is forecasted to grow at a CAGR of 7.6 percent and it is estimated to reach $22.8 billion by 2020
• Regions, such as Europe and North America, have high market maturity, while APAC is expected to experience high market growth
• Key drivers for BI include big data analytics, demand for data-as-a-service, and desire for personalized and self-service BI capabilities. However, implementation cost is a major constraint for the market but the emergence of cloud deployments is expected to mitigate this

BREXIT - Impact on Business Intelligence

Impact Area: IT Service Providers and Buyers

• Talent crunch in specific skills for application development and maintenance, can have an impact on external consultants' billing rates
• The UK technology startups have a significant workforce from EU member states. The UK does not have sufficient math and science graduates to fill positions in application development and engineering

Impact Area: SaaS Service Providers

• The UK remains one of the key destinations for datacenters serving EU clients. Despite the exit from EU, UK companies have to abide by EU General Data Protection Regulations(GDPR) which is set to become law in May 2018
• In addition to local regulations, UK companies managing EU data need to adhere to more stringent GDPR regulations which is expected drive compliance costs

Business intelligence Market Analysis Overview

Business intelligence is an approach that enables access and analysis of information based on data, to improve and optimize business decisions and performance using a fact-based support system. The major components of business intelligence solutions are as follows:

• Data mining
• Statistical analysis and visualization
• Data warehouse/data Mart
• Data sources

BI Implementation

Requirement Analysis

● Requirement analysis from all stakeholders, including business and system users
● Source and system analysis

Infrastructure Evaluation
● Evaluates technology architecture, such as data architecture, SLAs, workload modeling
● ETL architecture and database design

Design
● BI/OLAP report design
● Metadata solution design
● ETL and data quality management
● Logical and physical database design

Development
● Backup & recovery, failover and maintenance scripts
● Develop report, delivery mechanism, user interfaces

Testing and Deployment
● Create test environment and conduct integration/system/UAT testing
● Training and beta testing and final & complete deployment

Global BI - Industry Trends

● Mobile BI, data visualization and advanced analytics are top drivers of BI market
● More than 50 percent of large enterprises will have access to self-service BI tools for real-time data and better analysis

There is a significant technology shift in BI and analytics platforms as observed below:
● Data analysis has extended to free-form text exploration, rather than being restricted to structured ad hoc reporting and analysis, based on a predefined model
● Content authoring is more business-user driven 
● Emergence of cloud has led to greater adoption led by line of business managers as opposed to IT
● Dashboards, data visualization, analytics databases/platforms and BI/OLAP tools are the major functionalities in a BI solution, with maximum utilization in an enterprise.      Actionable insights are being delivered as intuitive dashboards through a seamless sharing and collaboration environment
● Self-service BI capabilities driven by global search and guided navigation have facilitated faster turnaround times for line of business managers
● IoT and BYOD have increased the data volume exponentially and are emerging trends in BI solution
● It is expected that by 2020, there will be 45 billion connected devices and a 42-percent increase in data volume every year, which poses a huge business opportunity for the BI market

Global BI - Drivers and Constraints

Drivers

Increasing need for Big data analytics

• Every day, the volume of big data creation amounts to 2.4 Quintillion bytes. By 2020, the amount of data generated is expected to reach 40 ZB (Zettabyte, i.e., 270 bytes). The exponential growth of data (volume, veracity, velocity) and needs mastering analytics to derive meaningful insights

Predictive/Prescriptive Analytics Tools

• BI analysis has been enhanced through the use of predictive and prescriptive analytics tools. Forecasting, graph analysis, and complex event processing techniques are used to improve the decision-making process

Data Storytelling
● Enterprises have adopted data storytelling capabilities to improve data interpretation and business decision making from key data insights
Automated Data Science
● BI technologies are leveraging automated data science technologies to assist enterprises with improved data categorization, segregation, sorting, analysis and
reporting

Visual Analytics

• Advanced visual data discovery tools have assisted enterprises in creating interactive dashboards for high volume of critical data

Natural Language Processing boost to self-service

• NLP based search extended to text and voice analytics is starting to gain prominence facilitating topline managers to quickly input analytical queries

Constraints

Digital Ethics

Data security breaches and issues result in a significant loss for enterprises. Cloud BI tools and integration with third-party applications with lack of secure framework may increase potential data breach opportunities

Data Governance

• With the emergence of cloud, there would be increasing cases of fragmented analytics deployments (smaller scale) driven by LOB managers as opposed to centralized IT. This can create challenges in maintaining data governance. Hence suppliers also need to focus on enhancing data audit features

High implementation cost

• Rising demand, complex programming, data integration and growing implementation costs result in price increase, which acts as a constraint in this market. Enterprise BI deployment and associated TCO are one of the barriers in adoption of BI technology by enterprises though this is being mitigated by the emergence of cloud deployments