Businesses now rely on data for analytics, machine learning, decision making, etc. Data is stored and analyzed using a wide range of sources, such as data lakes, data warehouses, etc. The data needs to be processed first before it is loaded into these sources. These processes encompass data discovery, extraction, cleaning, and preparation, among others.
AWS Glue is a serverless ETL service that deals with data discovery, data transformation, and data preparation so it can be effectively utilized by other services. In order to assist with data integration, AWS Glue provides both visual and code-based interfaces. The AWS Glue Data Catalog enables users to quickly search for and retrieve data. With a few clicks in AWS Glue Studio, ETL developers can graphically construct, run, and monitor ETL operations.
With more than 150+ certified AWS experts, Tiger Analytics has successfully implemented AWS Glue along with other AWS services for customers across different industry verticals.
Get better real-time data processing, allowing for faster decision-making and more efficient resource utilization
Outcomes of data exploration can be a powerful factor in understanding the structure of data, values distributions, and interrelationships
Get the benefit of faster speed, scalability and efficiency
Utilize our service for improved data efficiency, reduced risk of error and improved data analysis
Open-Source framework for Data Quality. It is highly configurable with table & field level rules, integrated with Airflow and monitoring tools.
New-gen ETL tools on cloud like AWS Glue provide a complete integration ecosystem enabling customers to build scalable lakes and lake houses for data analysis, process petabytes of data in batch and real-time using Apache Spark and migrate from expensive traditional ETL solutions to gain flexibility and reduce costs.
Enable faster time-to-value for business users, higher productivity for data engineering and operations, and greater governance and compliance fidelity. With a data fabric built, one can hyper-automate data discovery, data governance, and data consumption on AWS.