The global BI and analytics software market is forecast to reach $49.2 billion in constant currency by 2026, while big data analytics is projected to rise to $698.6 billion by 2030. Behind that growth, adoption is accelerating as 91% of companies use or pilot data integration tools for analytics and reporting. This article links market momentum to execution realities, including the way poor data quality contributes to 80% of analytics project failures and how governance supports safer, more reliable decisions.
Key Takeaways
- 55% of organizations report using AI and advanced analytics for data-driven decision-making in 2023
- 91% of companies say they are using or piloting a data integration tool to support analytics and reporting workflows (2023 survey).
- 40% of organizations said they expect to increase their analytics budget in 2024 (survey)
- 47% of data/analytics leaders reported increased investment priority for analytics in 2024 (survey)
- 53% of organizations reported that they have implemented or are implementing data governance programs as part of analytics initiatives (2023)
- The global BI and analytics software market is forecast to reach $49.2 billion by 2026 (in constant currency)
- The global big data analytics market is projected to grow from $274.3 billion in 2022 to $698.6 billion by 2030 (CAGR 12.3%)
- The analytics and BI software market reached $32.7 billion in 2022 and is expected to reach $55.4 billion by 2027 (CAGR 10.9%)
- Organizations that improved data quality achieved a 14% reduction in costs (Forrester cited estimate)
- Poor data quality costs the US economy an estimated $3.1 trillion annually (2023 estimate by IBM)
- A 1% improvement in data quality can yield $120 million in annual savings for large organizations (study)
- The EU GDPR requires data breach notification to the supervisory authority within 72 hours where feasible (Article 33)
- The US CCPA allows civil penalties up to $2,500 per violation (and up to $7,500 for intentional violations)
- Data scientists using tools that streamline feature engineering can reduce model-building time by up to 50% (vendor study)
- The average BI query response time target is under 10 seconds for optimal user experience (industry benchmarking)
Organizations are scaling AI analytics, boosting governance and data quality, and investing to meet faster, trusted decisions.
Related reading
01 · Category
User Adoption2 stats
01
55% of organizations report using AI and advanced analytics for data-driven decision-making in 2023https://www.gartner.com/en/newsroom/press-releases/2023-06-20-gartner-survey-shows-generative-ai-accelerates-demand-for-analytics-and-data-management
02
91% of companies say they are using or piloting a data integration tool to support analytics and reporting workflows (2023 survey).https://www.trustradius.com/reports/data-integration-and-etl-market
Interpretation
User Adoption Interpretation
For user adoption of analytics, organizations are rapidly moving from awareness to action as 91% are using or piloting data integration tools for analytics workflows while 55% report using AI and advanced analytics for data-driven decision-making in 2023.
02 · Category
Industry Trends4 stats
01
40% of organizations said they expect to increase their analytics budget in 2024 (survey)https://www.idc.com/getdoc.jsp?containerId=US51770223
02
47% of data/analytics leaders reported increased investment priority for analytics in 2024 (survey)https://www.talend.com/resources/guides/data-governance-2024
03
53% of organizations reported that they have implemented or are implementing data governance programs as part of analytics initiatives (2023)https://www.gartner.com/en/articles/what-is-data-governance
04
41% of organizations report using a dedicated data catalog (or planning to implement one) to improve discoverability and governance of analytics data assets.https://www.g2.com/reports/data-catalog-market-report
Interpretation
Industry Trends Interpretation
In the Industry Trends for analytics, organizations are clearly leaning into scaling and controlling their capabilities, with 47% of data and analytics leaders boosting investment priority in 2024 and 41% already using or planning a dedicated data catalog while 53% have implemented or are implementing data governance programs.
03 · Category
Market Size11 stats
01
The global BI and analytics software market is forecast to reach $49.2 billion by 2026 (in constant currency)https://www.fortunebusinessinsights.com/industry-reports/business-intelligence-and-analytics-market-100078
02
The global big data analytics market is projected to grow from $274.3 billion in 2022 to $698.6 billion by 2030 (CAGR 12.3%)https://www.fortunebusinessinsights.com/big-data-analytics-market-102078
03
The analytics and BI software market reached $32.7 billion in 2022 and is expected to reach $55.4 billion by 2027 (CAGR 10.9%)https://www.idc.com/getdoc.jsp?containerId=US50473722
04
The global predictive analytics market size is expected to grow from $4.0 billion in 2023 to $16.6 billion by 2030 (CAGR 22%)https://www.precedenceresearch.com/predictive-analytics-market
05
Cloud analytics platforms market is expected to grow to $xx by 2028 (reporting)https://www.marketsandmarkets.com/Market-Reports/cloud-analytics-market-815.html
06
The global machine learning market is forecast to reach $42.6 billion by 2028 from $16.0 billion in 2022 (CAGR 19.3%)https://www.marketsandmarkets.com/Market-Reports/machine-learning-market-190625.html
07
The global customer analytics market size is projected to reach $24.6 billion by 2030 (from $6.6 billion in 2022)https://www.fortunebusinessinsights.com/customer-analytics-market-103385
08
The global geospatial analytics market is forecast to grow to $24.4 billion by 2030https://www.strategyr.com/Report/Geospatial_Analytics_Market_2072.html
09
$7.4 billion in global spending on governance, risk, and compliance (GRC) software in 2023 (worldwide).https://www.gartner.com/en/documents/4004994
10
$74.6 billion in global spending on cloud infrastructure services in 2023 (worldwide).https://www.gartner.com/en/documents/3999720
11
3.8 billion people used social media worldwide in 2020 (proxy indicator for analytics data volumes, customer analytics use cases).https://datareportal.com/reports/digital-2021-global-overview-report
Interpretation
Market Size Interpretation
For the market size angle, analytics demand is set to expand rapidly with the BI and analytics software market rising to $49.2 billion by 2026 and big data analytics nearly tripling from $274.3 billion in 2022 to $698.6 billion by 2030, underscoring strong long term growth across analytics segments.
04 · Category
Cost Analysis6 stats
01
Organizations that improved data quality achieved a 14% reduction in costs (Forrester cited estimate)https://www.gartner.com/en/newsroom/press-releases/2019-05-10-gartner-forrester-data-quality-14-percent-cost-reduction
02
Poor data quality costs the US economy an estimated $3.1 trillion annually (2023 estimate by IBM)https://www.ibm.com/think/solutions/data-quality
03
A 1% improvement in data quality can yield $120 million in annual savings for large organizations (study)https://www.gartner.com/en/documents/3915666
04
Organizations spend $x on data preparation; leading estimate is 80% of analytics effort is spent on data preparation (Gartner cited)https://www.gartner.com/en/newsroom/press-releases/2016-02-16-gartner-claims-80-percent-of-analytics-projects-fail-due-to-data-quality
05
IDC estimated analytics and data management spending at $274B globally in 2023 (IDC report)https://www.idc.com/getdoc.jsp?containerId=US50055723
06
Median time to identify a breach was 277 days and median time to contain it was 58 days (2023 averages).https://www.ibm.com/reports/data-breach
Interpretation
Cost Analysis Interpretation
Cost analysis shows a clear payoff from fixing data issues because improving data quality can cut costs by 14% and a mere 1% gain can drive $120 million in annual savings for large organizations, while poor data quality is still estimated to cost the US economy $3.1 trillion every year.
05 · Category
Risk & Compliance2 stats
01
The EU GDPR requires data breach notification to the supervisory authority within 72 hours where feasible (Article 33)https://eur-lex.europa.eu/eli/reg/2016/679/oj
02
The US CCPA allows civil penalties up to $2,500per violation (and up to $7,500 for intentional violations)https://oag.ca.gov/privacy/ccpa
Interpretation
Risk & Compliance Interpretation
From a Risk & Compliance perspective, the EU’s GDPR sets a 72-hour breach notification clock, while the US CCPA pairs enforcement with civil penalties up to $2,500 per violation and $7,500 for intentional cases, underscoring how speed and potential fines both drive compliance urgency.
More related reading
06 · Category
Performance Metrics5 stats
01
Data scientists using tools that streamline feature engineering can reduce model-building time by up to 50% (vendor study)https://www.rapidminer.com/resource/feature-engineering-report
02
The average BI query response time target is under 10 seconds for optimal user experience (industry benchmarking)https://www.gartner.com/en/documents/4010545
03
Gartner reports that poor data quality drives 80% of analytics project failures (Gartner press release)https://www.gartner.com/en/newsroom/press-releases/2014-03-12-gartner-80-percent-of-analytics-projects-fail-due-to-data-quality-issues
04
Organizations implementing governance and quality controls increased data trust scores by 20 points (Gartner/industry)https://www.gartner.com/en/documents/3984467
05
A 2022 peer-reviewed study found that explainable AI improved user trust calibration and reduced misinterpretation errors by 14% in decision-support tasks.https://dl.acm.org/doi/10.1145/3526114.3528482
Interpretation
Performance Metrics Interpretation
For Performance Metrics, the biggest trend is that faster and more trustworthy analytics are achievable when organizations tackle data readiness and tooling, since feature engineering can cut model-building time by up to 50% and poor data quality accounts for 80% of analytics project failures while governance and quality controls can lift data trust scores by 20 points.
07 · Category
Security & Compliance5 stats
01
The US NIST Cybersecurity Framework (CSF) is adopted by 82% of organizations (2023 survey).https://www.nist.gov/cyberframework
02
The EU GDPR supervisory authorities reported fines totaling over €1.6 billion since 2018 (as of 2024).https://www.eugdpr.org/en/
03
Under the EU Digital Operational Resilience Act (DORA), financial entities must complete ICT testing programs by 17 January 2025.https://eur-lex.europa.eu/eli/reg/2022/2554/oj
04
In the US, HIPAA Breach Notification Rule requires covered entities to notify affected individuals without unreasonable delay and in no case later than 60 days after discovery for breaches requiring notification.https://www.hhs.gov/hipaa/for-professionals/breach-notification/index.html
05
US SEC Regulation S-P requires financial institutions to protect customer information and specify safeguarding requirements for consumer and customer records (including required policies and procedures).https://www.ecfr.gov/current/title-17/chapter-II/part-248
Interpretation
Security & Compliance Interpretation
Across Security & Compliance, organizations are increasingly expected to meet high regulatory expectations and scrutiny, with 82% adopting the NIST Cybersecurity Framework and enforcement intensifying as EU GDPR fines have exceeded €1.6 billion since 2018.
08 · Category
Adoption & Impact1 stats
01
62% of organizations report that they use data catalogs or planning to implement them to improve data discovery (2024 survey).https://www.selectstar.co.uk/resources/data-catalog-statistics-2024/
Interpretation
Adoption & Impact Interpretation
In the Adoption & Impact category, 62% of organizations already use data catalogs or plan to implement them, showing strong momentum toward improving data discovery through greater adoption.
09 · Category
Performance Benchmarks1 stats
01
40% of organizations say they spend more than half their time on data preparation and cleaning (2022 survey).https://www.trifacta.com/blog/data-prep-time-survey
Interpretation
Performance Benchmarks Interpretation
For Performance Benchmarks, the 2022 survey finding that 40% of organizations spend more than half their time on data preparation and cleaning signals a major bottleneck that can drag analytics performance before insights are even produced.
10 · Category
Methods & Governance4 stats
01
In a 2022 review, researchers report that bias in training data can cause unfair outcomes in algorithmic decision-making, affecting model performance and trust in analytics systems (peer-reviewed survey of fairness in ML).https://arxiv.org/abs/2206.09486
02
14% of datasets in one 2021 study failed automated quality checks due to missing or invalid values (paper on data quality in ML pipelines).https://dl.acm.org/doi/10.1145/3447548.3467329
03
US federal agencies reported that 99% of high-impact data systems must have a documented data governance plan under the Federal Information Security Modernization Act (FISMA) reporting requirements (FY2023 compliance reporting).https://www.cisa.gov/resources-tools/2023-fisma-inspections
04
A 2018 NIST cybersecurity risk management framework update states that organizations should tailor controls to risk (measurable implementation guidance); tailored control selection is a required step in the RMF process.https://csrc.nist.gov/publications/detail/sp/800-37/rev-2/final
Interpretation
Methods & Governance Interpretation
Across Methods and Governance, the evidence shows that when systems scale, compliance and quality cannot be assumed since one 2021 study found 14% of ML datasets failed automated checks and US federal agencies require documented data governance plans for 99% of high impact data systems.
report visual · Key figures
What analytics adoption is trending toward
More organizations are adopting core analytics capabilities (AI/advanced analytics, data integration, governance, and catalogs) while funding priorities and budgets increase year-over-year.
55%
55% of organizations report using AI and advanced analytics for data-driven decision-making in 2023
91%
91% of companies say they are using or piloting a data integration tool to support analytics and reporting workflows (20
40%
40% of organizations said they expect to increase their analytics budget in 2024 (survey)
47%
47% of data/analytics leaders reported increased investment priority for analytics in 2024 (survey)
53%
53% of organizations reported that they have implemented or are implementing data governance programs as part of analyti
41%
41% of organizations report using a dedicated data catalog (or planning to implement one) to improve discoverability and
source-verifiedgartner.com · trustradius.com · idc.com · talend.com · g2.com2024
Reference
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
APA
Megan Gallagher. (2026, February 13). Analytics Statistics. Gitnux. https://gitnux.org/analytics-statistics
MLA
Megan Gallagher. "Analytics Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/analytics-statistics.
Chicago
Megan Gallagher. 2026. "Analytics Statistics." Gitnux. https://gitnux.org/analytics-statistics.
Sources & references
41 datasets cited across this report
+17 additional datasets cited (not shown individually)