This is the first step in any analytical journey. It involves summarizing and visualizing historical data to understand what has happened in the past. It provides insights into patterns, trends, and relationships within the data. Descriptive analysis helps us understand “what happened” through data analysis. The primary objective of descriptive analysis is to simplify complex data into easier interpretation to offer a foundation of deeper exploration and informed decision-making.
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+91-9922310317
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Data Analytics / Machine Learning / Data Science
Join our journey where we transform your raw, complex, diverse, and unstructured data into cutting-edge data science solutions and pave the way for strategic growth and transformation. To get the best out of data we the right mixture of open-source frameworks. We have significant R&D and knowledge in the areas of LLMs, Computer vision, and NLP with the objective of building solutions for customers and helping support businesses in real-time decision-making.
At PDB Data science we utilize these simple but effective steps to provide effective solutions
- Discovering and defining the business problem
- Data collection and preparation
- Data exploration and visualization
- Data modeling and analysis using the right data and features
- Interpretation and decision–making
- Communicate Results/Publish Insights
We focus on
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Descriptive analysis
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Predictive analysisUses historical data and statistical algorithms to make predictions about future events or outcomes. It helps forecast trends, identify potential risks or opportunities, and optimize decision-making. Predictive analysis helps us forecast “what might happen” as it is all about looking into future. It is perfect for planning and strategizing. The key characteristics of predictive analysis includes statistical modeling, probability and forecasting.
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Fraud DetectionPlays a crucial role in detecting fraudulent activities by analyzing patterns and anomalies in transactional data. It helps identify suspicious behaviors, detect fraudulent transactions, and minimize financial losses. Fraud detection is a vital component of risk management that will contribute to the decision-making capabilities of an organization.
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Perspective AnalyticsPrescriptive analytics goes beyond predicting future outcomes. It suggests the best course of action to achieve the desired result. It uses optimization algorithms and simulations to determine the optimal decision or solution. Perspective analysis helps us understand “what should be done”. The main characteristics of perspective analysis are optimization and decision support.
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Diagnostic AnalyticsFocuses on analyzing data to determine why certain events or outcomes occurred. It involves exploring correlations and causal relationships to identify the factors that influenced a particular result. Diagnostic analysis helps us understand “why it happened”. The key characteristic of diagnostic analysis is to find root cause analysis and compare datasets or variables to uncover patterns and correlations.
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Dashboard exploration and VisualizationData analytics involves exploring and visualizing data to uncover patterns, trends, and anomalies. Visualizations such as charts, graphs, and dashboards make it easier to understand complex data and communicate insights effectively.
