In today’s world, business heavily relies on data. With the businesses gaining momentum, the amount of data that needs to be analyzed is growing enormously and massively every day. An adequate data analytics process helps businesses in gaining meaningful insights, enhance decision making capabilities, improve operational inefficiencies, etc.
Businesses build data solutions like databases, data lakes, data warehouses, etc in separation with their own data management, data storage, and ingestion layers. Which results in data silos, data management complexity, data consistency issues. These challenges avert businesses from utilizing the data, getting the insights. To overcome these challenges AWS provides various data and analytics services which helps in managing, storing and utilizing the data seamlessly. Few AWS data and analytics – Amazon Athena, Amazon EMR, Amazon OpenSearch Service, Amazon Kinesis, and Amazon Redshift. With more than 170+ certified AWS experts, Tiger Analytics has successfully implemented AWS data and analytics services for numerous customers across various industry verticals.
Data Warehousing and Business Intelligence
Amazon Redshift enables organizations to build scalable data warehouses for efficient querying and analysis. Businesses can leverage tools like Quicksight to visualize data, generate reports, and gain actionable insights to drive strategic decisions.
Real Time Analytics
Services like Amazon kinesis allow companies to process and analyze streaming data in real-time. This is crucial for applications such as fraud detection, real-time monitoring, and dynamic pricing, where immediate data insights are necessary.
Big Data Processing
AWS provides solutions like AWS Glue and Amazon EMR (Elastic MapReduce) to handle large-scale data processing tasks. These services facilitate data extraction, transformation, and loading (ETL) processes, enabling organizations to manage and analyze vast datasets effectively.
Data Migration and Integration
AWS Database Migration Service (DMS) and AWS Glue help organizations migrate data from on-premises databases to the cloud, and integrate diverse data sources. This ensures seamless data consolidation, reduced infrastructure costs, and enhanced data accessibility across the organization.
AWS Self-Service Data Warehouse Management
Provides end to end capability right from Data Quality and transformation capabilities required for a Data Analytics.
Great Expectations
Data Quality Framework: Open-Source framework for Data Quality. It is highly configurable with table & field level rules, integrated with AWS tools and services.
Data and Analytics Platform Leveraging Amazon Redshift for a Global Pharmaceutical Major
Our client, a prominent global pharmaceutical firm headquartered in the United States was relying on an on-premises infrastructure. The client faced a prolonged process which often span into weeks, for infrastructure setup. The client aspired to establish a centralized, resilient, standardized cloud data ecosystem as part of their strategic vision.
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Transforming Time-to-Market & Data Processing for a Global Mobility Solutions Leader
Our client is a leading global provider of mobility solutions. They faced challenges with slow time-to-market, data inefficiencies, and bottlenecked processes. They sought to streamline dashboarding processes, establish a standardized data ingestion mechanism, enhance their time-to-market, and optimize SQL data processing.
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