Analytics and Business Intelligence (ABI) platforms are evolving rapidly, driven by AI advancements and integration with cloud ecosystems. These platforms empower users—ranging from IT professionals to business analysts and consumers—to visualize, analyze, and govern data.
Modern ABI platforms provide a range of capabilities:
- Data Visualization: Interactive dashboards for exploring and presenting data.
- Governance: Ensures data security and controlled sharing.
- Data Preparation: Drag-and-drop interfaces for blending and preparing data.
- AI and Machine Learning: Integration for predictive analytics and automated insights.
- Natural Language Query (NLQ): Allows users to interact with data conversationally.
- Collaboration: Tools for co-producing analytics projects across teams.
Market Overview
In 2024, vendors are prioritizing generative AI and composable analytics, enabling users to create insights with minimal technical expertise. ABI platforms are also integrating closely with cloud ecosystems to streamline data pipelines and decision-making processes.
Magic Quadrant Categories
Vendors are classified into four categories based on Ability to Execute and Completeness of Vision:
- Leaders:
- Microsoft (Power BI): Market leader with strong pricing, Azure integration, and AI-powered features like Copilot.
- Google (Looker): Combines robust semantic modeling with seamless integration into Google Cloud’s data and AI tools.
- Salesforce (Tableau): Focused on visual exploration and augmented analytics.
- Challengers:
- Amazon Web Services (QuickSight): Excellent integration with the AWS ecosystem but limited to AWS deployment.
- Domo: A strong choice for SMBs with its user-friendly architecture and marketing analytics focus.
- Visionaries:
- SAP (Analytics Cloud): Integrates seamlessly with SAP business apps but sees limited adoption outside the SAP ecosystem.
- SAS (Viya): Offers AI-driven capabilities but struggles with pricing transparency.
- Niche Players:
- Sisense: Known for embedded analytics and developer-first principles but lacks broader ecosystem integration.
- Tellius: Excels in NLQ and automated insights but is less competitive in reporting and data visualization.
Strengths and Challenges Across Vendors
While Microsoft Power BI dominates the market through its integration with Microsoft 365, other vendors like Google Looker and Tableau focus on composability and generative AI. Smaller players such as Incorta and ThoughtSpot are carving niches in areas like operational reporting and augmented analytics.
However, challenges persist: many platforms face gaps in vertical-specific solutions, global reach, and user-friendly AI capabilities. Vendors like Qlik and Spotfire are addressing these gaps by expanding AI integration and offering modular, cloud-agnostic tools.
Trends Shaping ABI in 2024
- Generative AI: Transforming user interfaces with conversational data exploration and automation.
- Multicloud and Openness: Ensuring interoperability across diverse cloud environments.
- Citizen Developers: Platforms are catering to non-technical users with low-code/no-code tools for creating insights and workflows.
Businesses must balance cost, technical capabilities, and vendor alignment with long-term goals. Leaders like Microsoft and Google offer comprehensive solutions, while Visionaries and Niche Players often specialize in addressing unique industry needs.
As ABI platforms continue to evolve, their role in decision-making and organizational growth will only expand. Selecting a platform with the right mix of capabilities and ecosystem integration will be critical for success.
How to calculate companies in magic quadrant ?
Gartner evaluates companies for inclusion in the Magic Quadrant using a robust methodology. The analysis is based on two main dimensions:
- Ability to Execute
- Completeness of Vision
Here's how the evaluation typically works:
1. Ability to Execute
This dimension measures a company’s ability to deliver its products and services to customers effectively. It includes:
- Product or Service Quality: Features, performance, and capabilities of the company’s offerings.
- Market Responsiveness: The company's ability to respond to market dynamics and customer needs.
- Customer Experience: Client satisfaction, user reviews, and support effectiveness.
- Operations: The company’s infrastructure, resources, and organizational stability.
- Sales and Pricing: The effectiveness of sales strategies and pricing models.
- Financial Viability: The company’s financial health and capacity to sustain growth.
Gartner collects data from customers, partners, and public financial reports to assess these criteria.
2. Completeness of Vision
This dimension evaluates the company’s innovation, strategy, and ability to drive future industry trends. Key factors include:
- Market Understanding: Knowledge of customer needs and market trends.
- Marketing and Sales Strategy: Effectiveness of go-to-market approaches.
- Product Strategy: Innovation in technology and alignment with customer needs.
- Business Model: Alignment of strategy with revenue generation.
- Industry Vision: The ability to anticipate and shape market changes.
- Ecosystem Development: Partnerships, collaborations, and developer communities.
Gartner reviews roadmaps, plans, and innovation pipelines to judge this dimension.
3. Weighting and Placement
Gartner assigns weights to the evaluation criteria based on the industry being assessed (e.g., analytics, cloud computing, cybersecurity). Companies are scored, and their placement in the Magic Quadrant is based on their scores in these dimensions:
- Leaders: High ability to execute and completeness of vision.
- Challengers: High ability to execute but less completeness of vision.
- Visionaries: High completeness of vision but lower ability to execute.
- Niche Players: Lower in both dimensions, typically focusing on a specialized market or region.
4. Research and Verification
- Customer Feedback: Gartner gathers direct feedback from end-users, often via surveys or interviews.
- Market Analysis: Analysts review market trends and competitors’ movements.
- Data Validation: Companies are asked to submit data, product demonstrations, and reference customers.
5. Outcome
The final Magic Quadrant report includes:
- A visual representation of the quadrant.
- A detailed analysis of each company's strengths and cautions.
- Market trends and predictions.
Gartner does not publicly disclose a precise formula for calculating positions in the Magic Quadrant because it involves qualitative and quantitative factors assessed by analysts. However, the evaluation can be broadly described as a weighted scoring system applied to the two dimensions:
- Ability to Execute
- Completeness of Vision
Here’s a general conceptual breakdown:
1. Ability to Execute (Y-axis):
Ability to Execute Score=∑(Wi×Si)\text{Ability to Execute Score} = \sum \left( W_i \times S_i \right)Ability to Execute Score=∑(Wi×Si)
- WiW_iWi: Weight assigned to each criterion (e.g., product quality, customer experience, financial viability, etc.).
- SiS_iSi: Score given by Gartner analysts for that criterion.
For example, the weights might look like this:
- Product quality: 25%
- Customer experience: 20%
- Financial viability: 15%
- Sales execution: 10%
- Market responsiveness: 10%
- Operations: 10%
- Marketing execution: 10%
The weighted scores are summed to calculate the company’s overall Ability to Execute score.
2. Completeness of Vision (X-axis):
Completeness of Vision Score=∑(Wi×Si)\text{Completeness of Vision Score} = \sum \left( W_i \times S_i \right)Completeness of Vision Score=∑(Wi×Si)
- WiW_iWi: Weight assigned to each criterion (e.g., product strategy, market understanding, business model, etc.).
- SiS_iSi: Score given by Gartner analysts for that criterion.
For example, the weights might look like this:
- Market understanding: 25%
- Product strategy: 20%
- Innovation: 15%
- Business model: 10%
- Marketing strategy: 10%
- Ecosystem development: 10%
- Sales strategy: 10%
The weighted scores are summed to calculate the company’s overall Completeness of Vision score.
3. Placement in the Quadrant:
The final placement is determined by plotting the two scores on a graph:
- Y-axis: Ability to Execute score.
- X-axis: Completeness of Vision score.
Quadrant Placement:
- Leaders: High scores on both axes.
- Challengers: High Y-axis (Execution), lower X-axis (Vision).
- Visionaries: High X-axis (Vision), lower Y-axis (Execution).
- Niche Players: Lower scores on both axes.
Score=∑i=1nWi×Si\text{Score} = \sum_{i=1}^{n} W_i \times S_iScore=i=1∑nWi×Si
Where:
- nnn = number of evaluation criteria.
- WiW_iWi = weight of criterion iii (depends on industry and category).
- SiS_iSi = analyst’s score for criterion iii.
Example (Hypothetical):
Company A:
- Ability to Execute:
- Product Quality (W=0.3,S=8/10W = 0.3, S = 8/10W=0.3,S=8/10): 0.3×8=2.40.3 \times 8 = 2.40.3×8=2.4
- Customer Experience (W=0.2,S=9/10W = 0.2, S = 9/10W=0.2,S=9/10): 0.2×9=1.80.2 \times 9 = 1.80.2×9=1.8
- Financial Viability (W=0.15,S=7/10W = 0.15, S = 7/10W=0.15,S=7/10): 0.15×7=1.050.15 \times 7 = 1.050.15×7=1.05
- Total: 2.4+1.8+1.05+⋯=7.252.4 + 1.8 + 1.05 + \dots = 7.252.4+1.8+1.05+⋯=7.25
- Completeness of Vision:
- Market Understanding (W=0.25,S=8/10W = 0.25, S = 8/10W=0.25,S=8/10): 0.25×8=2.00.25 \times 8 = 2.00.25×8=2.0
- Product Strategy (W=0.2,S=9/10W = 0.2, S = 9/10W=0.2,S=9/10): 0.2×9=1.80.2 \times 9 = 1.80.2×9=1.8
- Innovation (W=0.15,S=7/10W = 0.15, S = 7/10W=0.15,S=7/10): 0.15×7=1.050.15 \times 7 = 1.050.15×7=1.05
- Total: 2.0+1.8+1.05+⋯=6.852.0 + 1.8 + 1.05 + \dots = 6.852.0+1.8+1.05+⋯=6.85
Company A would be plotted at (6.85, 7.25).
This weighted scoring ensures that companies are evaluated fairly based on a mix of qualitative and quantitative data. However, the actual weights and scoring criteria are customized by Gartner analysts for each industry and report.