Data Engineering & Analytics
Data Engineering & Analytics

Our data engineers design, build, and manage big data infrastructures, focusing on the data architecture needed for reporting and keeping data processing systems performing efficiently.

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Data Engineering & Analytics

Data engineering is the form of data science that targets practical applications of data collection and analysis.

Organizations across the globe deal with massive data generated from IoT devices, connected systems, and users. Data comes in all sizes and shapes– both structured and unstructured forms leaving most unused. To stay competitive, it is important for organizations to align data strategy with their business goals and adopt organizationwide data culture to get data-driven insights from data for decision-making and accelerated business growth. With the right data engineering services, organizations can monetize and maximize the value of their data assets.

DATAABSOLUTE offers the following services in Data Engineering & Analytics :

DATAABSOLUTE offers the following services in Data Engineering & Analytics
  • Data Management – Data Integration, Data warehousing, Data Lakes / Big Data & Architecture
  • Data Governance – Master Data Management, Data Quality, Data Governance Platform Migration
  • Improvements & Innovations – Performance Improvement & Optimization
  • Analytics – Business Intelligence, Visualization/Reporting, and Machine Learning, Data Mining, Exploratory Data Analysis
  • Data Foundation – On-Premise, On Cloud, Infrastructure Upgrade & Migration, Server Upgrades, DBMS Upgrades

DATAABSOLUTE has helped companies to solve their data challenges, predict demand patterns, improve end-user satisfaction and guide them through business strategies based on intelligent insights. Our data engineering team analyzes structured, semistructured, and unstructured data with the right technology, processing tools, and approach. With our engineering expertise, we provide data engineering solutions for complete data lifecycle management, including data acquisition, storage, modeling and consultation, automated ETL processes, building pipelines, migration, integration, visualization, and analytics.

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