Many organizational initiatives are becoming cloud-based. Cloud engineering enables organizations to build
and maintain data lakes and data pipelines. Organizations aspiring to be data-driven need to focus on cloud- driven analytics.
Trigent enables organizations to not only leverage the power of cloud data warehouses and data lakes, but also build solutions with cloud-first architecture. 4Tekz's cloud data management services help organizations capture, store, analyze, and deliver high performance of large volumes of data for real-time data analytics workloads. Our teamm of data analysts helps organization , optimize costs and resources and design a cloud adoption strategy.
Data silos are a major challenge for organizations. The major focus of any organization generating humongous amounts of data daily is to extract it from numerous sources and integrate and load it into a data warehouse.
Our architecture will integrate new and existing data sources together into an effective data lake, either from scratch or by leveraging services provided by major cloud platform vendors. We will transform data from your existing systems into intelligence that enables you to ask questions and discover new opportunities that drive progress. We will also implement upstream and downstream ETL pipelines for batch processing or real- time processing. 4tekz's team of seasoned experts leaverages it's expertise in the end - to - end .
Data Engeneering ecosystem to select or recommend the appropriate technology stack for building data pipelines that are robust and generate faster insights .
Data lakes can ingest large volumes, varieties, and velocities of data and catalog them centrally. Data lakes in the cloud are a centralized repository of large amounts of structured and unstructured data that provide end- to
-end services to reduce the time effort, and overall cost of data analytics.
The aim of a data lake is to make organizational data accessible to a variety of end-users, such as data scientists, data analysts, and data engineers. Data lakes are built on low-cost hardware, making it economically viable to store large amounts of data.
Big data infrastructure on the cloud can be scaled up or down as needed, and cloud elasticity enables organizations to focus less on managing data platforms.
We ingest data from all sources into scalable data lakes. We assess and architect the ideal cloud architecture for your business across major providers like AWS Redshift, Microsoft Azure, Snowflake, and Google BigQuery.
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