Accelerate your team's data-first mindset for Digital Transformation.

Reduce learning barriers to data culture and increase contextuality for business.
Foundation pillars of Leap - Contextual, Experiential and Measurable
1200+
Data Problems
750+
Data Algorithms
30+
Business Domains
100+
Learning Maps
Higher user stickiness and engagement
Promote higher user stickiness and engagement

Through a gamified way of platform adoption and access.

Up-skilling through industry ready competencies
Up-skilling users through industry-ready competencies

For better client project deployment, hiring, promotions & harvesting.

Regular content updates and releases
Regular content updates and releases

By providing new data problems & algorithms across multiple business domains.

Integrable with tech and business ecosystem
Integrable with tech & business ecosystem

To give wider coverage of data sources and business information systems.

Efficient cross domain pollination
Efficient cross domain pollination

By giving users an easy path to enter newer areas of analytics.

Patent & Trademark Portfolio

LEAPS is a contextual AI platform enabled by Data
Analytics and Machine Learning Frameworks. It is built
using our patented design to support an iterative
Experiential Approach.

Cornerstones of LEAPS

Contextual

Contextuality in problem-solving refers to the ability of a system or platform to provide relevant and timely information to users based on their current context, including their goals, interests, and level of expertise.
By applying contextuality in problem-solving, problem solvers can develop solutions that are more effective and appropriate for the specific problem and its context. This can lead to better outcomes, greater stakeholder satisfaction, and improved organizational performance.

cornerstone of the leaps - contextual
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Experiential

Experiential approach emphasizes on the importance of learning through experience and reflection. It involves engaging learners in hands-on activities and projects that allow them to apply their knowledge and skills in real-world situations through simulations and virtual environments.



cornerstone of the leaps - Experiential
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Measurable

Measurable aspect infers to the quantification of each activity on the platform at individual user level, cohort level, enterprise level and client project level, through which progress, performance and personalization can be tracked and presented through relevant metrics. This helps in assessing timely ROIs on different analytics initiatives in the organization.

cornerstone of the leaps - measurable
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Contextuality providing common ground for data culture
Define business context through OKR
Learning Journeys and Maps
Define business context through OKR framework & industry maps

OKR is a goal-setting framework to define measurable goals. An 'objective' is a declaration of direction and intent, and the 'Key Result' is used to track the progress toward the objective. On the other hand, KPIs (Key Performance Indicators) monitor ongoing performance. By combining the OKR Framework with KPI-specific content and Business Maps, LEAPS enables businesses to leverage data science concepts for creating a robust framework to establish objectives across industries and monitor progress towards the specified goals. Industries can use this for implementing actions to improve performance and drive data-based decision-making.

Business domain - specific data problems and related algorithms
Hands-on Activities
Business Domain-Specific Data Problems and Related Algorithms

With an enormous variety of data being available, businesses are increasingly using the data to drive key decisions. Different forms of data problems have so far outpaced manual processing.
Simultaneously, numerous computer algorithms have been developed to integrate datasets for more extensive and deeper analyses. Using an algorithm already trained on industry and function-specific data, LEAPS allows learners to use industry-ready data/solutions and produce actionable and accurate insights in real-world situations across sectors. Business problems are translated into an AI and data science solution together with an iterative set of thought experiments, modelling techniques, and evaluations against the business goals.

Just in time assistance through personalized recommendations and expert support
Hands-on Activities
Just-In-Time Assistance Through Personalized Recommendations and Expert Support

The Visual Maps, Point-in-Click functionality, and the innovative approach of Learn-Apply-Solve offered by LEAPs allow users to independently experiment with the data science concepts with real-world case studies and track their performances and achievements.
LEAPS assists users throughout their journey on the platform. Different complexity levels of various data cases provide an actionable roadmap for users to solve AI and data science-based business problems. The recommendation engine constantly provides suitable function-related and other suggestions to users to provide real-time support. The expert support group and the SME calendarized sessions provide unique experiences to learners, simplifying their learning journeys through one-on-one suggestions and recommendations.

Interpretable path and execution checkpoints for better solutioning
Hands-on Activities
Interpretable Paths and Execution Checkpoints for Better Solutioning

LEAPS offers a Structured Learning approach to the users for learning and solving business problems.
The structural framework guides the users with suitable courses and specialization tracks to learn depending on their specific requirements. The milestone-based approach adopted by the platform directs the learner when a particular milestone is achieved. It returns an error message for the user to know if something is wrongly executed together with the appropriate recommendations for better solutions.

Our Trending Publications
A Guide to Customer Churn Prediction for Telecom Enterprises

Famous Jordanian businessman Talal Abu – Ghazaleh once said, “An efficient telecommunications network is a foundation upon which an information society is built.”Standing in the year 2023, it is safe to say that the information age is truly upon us. But alas, the telecom industry is in a never-ending turmoil owing to the sky-high competitive rivalry and the need for its enterprises to remain financially viable. As a matter of fact, that’s not even the end of the story.

How ML is helping insurance claims during natural calamities

Standing in 2022, we witnessed a worldwide epidemic along with numerous other natural calamities mere months ago. Not just that, records show that since 2017, there has been a steady increase in expenses incurred for natural disasters almost across the globe. During these phases, the insurance industry offered its services to millions of people each day. In fact, it is safe to assume that they witnessed sky-high premium volumes with no signs of slowing down. But the question here is how insurance companies manage the vast amount of data involved with these massive premiums.

Application of SVM in Breast Cancer Detection

Compared to the 1900s, it is safe to assume that, at present, the world healthcare system is at its peak. Modern medicine is making ground-breaking discoveries and tackling deadly diseases every step of the way. But no matter what, the battle against breast cancer keeps on raging against women globally.

Download Brochure / White Paper

Take a closer look at Analyttica’s flagship leadership development experience, explore a sample agenda, and read what our past alumni have to say about their experience and more in the Executive Program Brochure.

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Leadership Team

Rajeev Baphna founder and CEO of Analyttica and leaps
Rajeev Baphna
Founder, CEO
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Rajeev Baphna
Founder, CEO

Strategic Leadership and Vision Management of Overall Partnerships Executive Relationship Management Business Development Analytical SME and Thought Leadership.

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Rupal Baphna director and cao of Analyttica and leaps
Rupal Baphna
Director, CAO
Chaitanya Pathak chief technology officer
Chaitanya Pathak
Chief Technology Officer
Madhav Kaushik senior vice president of Analyttica and leaps
Madhav Kaushik
Senior Vice President
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Madhav Kaushik
Senior Vice President

Thought Leadership & Analytical SME | Analytica Transformation & Data Driven Decision Making | Enterprise Growth & Delivery | Product Strategy

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Koushal Udupa s chief of operations and finance manager of Analyttica and leaps
Koushal Udupa S
Chief Of Operations
& Finance Manager
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Koushal Udupa S
Chief Of Operations & Finance Manager

Experienced CA who is Competent, diligent & result oriented professional, offering experience across Accounts & Finance Management, Company & Partnership Firm Accounts, Tax Assessment, Computation of Taxes, Budgeting, Company Law Matters and Audit.

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Sridhar HR corporate services and it manager of Analyttica and leaps
Sridhar HR
Corporate Services
& IT Manager
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Sridhar HR
Corporate Services and IT Manager

Certified Security Analyst & Ethical Hacker with enough experience in IT operations and project management.

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