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Data Analytics

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Our Data Storage

Data Storage Technologies

Data analytics is the science of analyzing raw data to derive useful insights and conclusions from it. It involves applying various techniques and algorithms to uncover patterns, trends, correlations, and other meaningful information within the data. The goal of data analytics is to help organizations and businesses make informed decisions based on data-driven evidence.

Presenting the analyzed data in visual formats such as charts, graphs, and dashboards to make it easier to understand and interpret.

Cloud-Based Data Analytics

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01.
Data collection & processing

Structured & Unstructured IoT, Social Cloud, Mobile RDBMS

02.
Analytics & visualizations

Information Management Real-time Data, Self-Serve Dashboard, Advanced Reporting

03.
Data Operations

Structured & Unstructured IoT, Social Cloud, Mobile RDBMS

04.
Data Tech & Transformation

Technology Migrations, Data Migration to Hadoop, License Optimization

Data Collection & Processing

Structured & Unstructured IoT, Social Cloud, Mobile RDBMS.

Data collection is the foundational step in the data analytics process, involving the gathering of raw data from various sources to provide a comprehensive dataset for analysis. This data can come from a wide range of sources, including:

Data Rules

Data Transformation

Data Cleansing

Data Blending

Data Validation

Data Normalization

Data Association

Data Integration

Data Analytics & Visualization

Structured & Unstructured IoT, Social Cloud, Mobile RDBMS.

Data Processing Once the data is collected, it undergoes a series of processing steps to prepare it for analysis. Data processing involves cleaning, transforming, and organizing the raw data to ensure its quality and usability. Key steps in data processing include

Advanced Analytics

Self-Serve Analytics

Real Time Analytics

Information Management Portal

Data Operations

Data Security, Master Data Management, Data Governance

Data operations, often referred to as DataOps, encompass the practices, processes, and tools required to manage the end-to-end lifecycle of data within an organization.

Master Data Management

Data Governance

Data Security

Data Tech & Transformation

Technology Migrations, Data Migration to Hadoop, License Optimization

Data technology and transformation encompass the innovative tools, techniques, and processes that organizations use to convert raw data into valuable insights and actionable intelligence.

Environment Assessment

Data Discovery & Profiling

Migration Strategy

Data Migration

Data Validation

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