Data Analytics Prescience Decision Solutions November 22, 2022
OUR EXPERTISE
DATA ANALYTICS
We Help You Remove Roadblocks And Leverage Core Data Assets With The Implementation Of The Following Concepts.

The journey begins with an assessment that helps organizations identify their capabilities and adoption levels. We employ an AI maturity framework that evaluates your readiness across various dimensions, including overall strategy, budgeting, data, infrastructure, and more.
OUR SIMPLE WORK PROCESS
validation
Validation
External validation of the current challenges you have, and a clear way to bring them to attention.
simplification
Simplification
Exploiting your data and converting that asset into currency
prevention
Prevention
Complying with the laws, regulations and applicable codes
technology
Technology
Selecting the right tools, technology and architecture for your analytics initiatives

Get your data analytics questions answered

Our Analytics Consulting Services
At Prescience we come with pedigrees of creating and running analytics businesses for large technology and consulting companies — including TCS, Infosys, AIG, Mindtree, IBM & Microsoft.
We begin with a purposeful big picture thinking, align with your organizational strategic plan, conduct a systematic inventory and help create distinctive capabilities by calibrating available capability and industry benchmarking.
We determine who gets involved in what and define the structure, management and oversight of your analytics projects.
We can help formulate the optimal team mix by bringing together quantitative, technical, business, design and consulting skills. We can even tell you how to work with quants.
Good analytics requires relevant, contextual,timely and sufficiently granular data of good quality. We support your data strategy by providing inputs on aspects like data structure, uniqueness, reliability, integration and augmentation.
We can help formulate the optimal team mix by bringing together quantitative, technical, business, design and consulting skills. We can even tell you how to work with quants.
Untangle Your Data
Every business has questions that can be answered using data but as data explodes in quantity and complexity, companies find it difficult to unlock its full potential. Perhaps you’ve got your islands of analytics, or you are assembling data into a data hub or a data lake and have a mess on your hands or your challenge is more sensitive about data privacy or something can’t be done by an internal team because they lack the time or expertise
Resources
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Partner with Prescience to see your data come to life with expert analytics consulting

Frequently Asked Questions
Common analytics use cases across different industries include customer segmentation, sales forecasting, inventory optimization, and fraud detection. Data analytics offers actionable insights, helps identify trends, and optimize operations, which enables businesses to make informed decisions.

Summarization of past data to understand what has happened, is called Descriptive analytics. On the other hand, Predictive analytics involves statistical models to forecast future events.

Prescriptive analytics offers best strategies and potential solutions to anticipated challenges. It recommends actions based on predictive insights, guiding decision-making to achieve desired outcomes.

Using analytics solutions, you organize and analyze data collected from various sources, which gives you a comprehensive view of business performance and customer behavior. They help identify key performance indicators, monitor trends, and uncover patterns, enabling your business to improve operational efficiency, tailor marketing strategies, enhance customer experiences, and drive growth through data-driven insights.

Interpreting and visualizing results involves using dashboards, charts, graphs, and heat maps to create clear, comprehensible representations of data. These visualizations make complex data accessible, allowing stakeholders to quickly grasp insights, identify trends, and make informed decisions.

Common challenges include data quality issues, integrating disparate data sources, lack of skilled personnel, and data privacy concerns. To address these challenges, we recommend various data governance practices, ETL tools for data integration, investing in training and hiring skilled professionals, and complying with data protection regulations.