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Enterprises with significant investments in Teradata have been missing the cost and flexibility advantages of a modern big data architecture. To make the move, enterprises need to confront the complexity of converting Teradata workloads. Manual identification and transformation of EDW, ETL, analytical and reporting workloads is complicated, time-consuming, and error-prone.
Download our solution brief to learn how Impetus Teradata Workload Transformation Solution can simplify, automate and accelerate the ETL and EDW conversion process for your enterprise.
Continuous Integration and Delivery (CI/CD) is a set of automated SDLC practices and methods that enable frequent and error-free releases of change in code or data, with extensive visibility and traceability. Many enterprises are adopting an automated approach to accelerate and simplify the entire process of Extract, Transform, and Load (ETL).
StreamAnalytix is a self-service ETL and analytics tool that comprises of various features to support CI and CD. You can build production-grade continuous applications, which makes it easier to manage out-of-sync data, maintain greater consistency within data streams, and join streams with static data sources more efficiently.
This solution brief will provide you a snapshot of how to build, deploy, and deliver at high velocity with StreamAnalytix.
Read the solution brief to learn more.
Enterprises moving to Snowflake can experience benefits such as full SQL support, serverless architecture, strong partnerships with BI and ETL tools, and ease of maintenance. However, moving workloads from legacy environment to cloud has its own complexities.
Find out how the Impetus Snowflake Workload Transformation Solution can help you address these challenges and ensure agility and elasticity while moving to Snowflake.
To make the move to big data / cloud, you’ll need to confront the complexity of transforming Netezza warehouse workloads. Manual identification and transformation of EDW, ETL, analytical and reporting workloads is complicated, tedious, time-consuming, and error-prone. Read our solution brief to learn more about how we are simplifying that effort.
Data-driven decision making is changing the way businesses operate, and the data warehouse is at the core of an enterprise’s big data and analytics strategy. Existing data warehouses are neither easily scalable to accommodate exploding data volumes nor analytically flexible for business users and analysts.
As the traditional data warehouse falls short of today’s business requirements, there is a driving need to move to a cloud, on-premise, or hybrid big data warehouse environment. It is essential that we also eliminate the data silos that exist today and bring together enterprise-wide data to create a comprehensive single source of truth across the business.
This solution brief describes how you can:
Ever-increasing data volumes are fast outgrowing existing data warehouses. Enterprises are looking at offloading data and processing to a big data environment to address the challenges of existing data warehouses.
A comprehensive Assessment to identify database workloads, users, and applications for offloading is the first step in the journey to a modern big data warehouse. This document explores why Assessment is critical to your enterprise data warehouse migration strategy.
Read the IDW Assessment brief to learn:
