Solution Briefs

Manage modern data platforms on cloud or on-premise with AI-driven DevOps

Manage modern data platforms on cloud or on-premise with AI-driven DevOps

Learn how you can take advantage of our customized cloud services, innovative automation levers, advanced monitoring tools, and security best practices to seamlessly manage mission-critical use cases across on-premise and cloud environments.

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Intelligent and automated transformation of your enterprise data warehouse to Google Cloud Platform (GCP)

Intelligent and automated transformation of your enterprise data warehouse to Google Cloud Platform (GCP)

As a modern cloud platform, GCP empowers enterprises with improved scalability, greater elasticity, and reduced costs. However, the modernization journey can be time-consuming and error-prone.

Learn how our Automated Workload Transformation Solution de-risks the transformation of workloads onto GCP.

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Build a high-performing data ecosystem for ETL, ML, and BI — Accelerated and Unified

Build a high-performing data ecosystem for ETL, ML, and BI — Accelerated and Unified

Transform the decision-making capabilities of your business with accelerated insights from all your data. Our end-to-end solution helps you build a single, integrated pipeline to transform, ingest, and consume trillions of rows of data at a speed that was impossible before. It can read data from multiple sources in real-time, cleanse and enrich it quickly, and make it available for instant, multidimensional analytics across hundreds of dimensions and measures. Advanced algorithms, machine learning capabilities, and an automated workflow ensure that your data is put to work as soon as it arrives, and you can leverage every bit of it to expand your business.

Download our solution brief to learn how you can:

  • Build big data applications 5 to 10x faster
  • Analyze 1000x more data, on-premise and in the cloud
  • Enable your teams to work at 5x efficiency
  • Get 200x faster insights with 99% BI queries delivered in less than a second

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Automated Migration of Teradata ETL and EDW to Cloud

Automated Migration of Teradata ETL and EDW to Cloud

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.

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Leveraging continuous integration, delivery, and deployment (CI/CD) in StreamAnalytix

Leveraging continuous integration, delivery, and deployment (CI/CD) in StreamAnalytix

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.

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The data flow platform for ETL, analytics, and machine learning on the cloud

The data flow platform for ETL, analytics, and machine learning on the cloud

Visually build and deploy streaming and batch processing use cases rapidly, with the best-of-breed open source technologies, both on-premise and in the cloud.

StreamAnalytix is a multi-engine, enterprise-grade, visual platform for unified streaming and batch data processing, and machine learning. Use compute engines like Apache Spark (and more) as the underlying technology to ingest, blend, and process high-velocity data streams as they arrive. Run machine learning models, train and refresh models in real-time or in batch mode, visualize results on real-time dashboards, and raise corresponding real-time alerts and action triggers.

Why StreamAnalytix?

Build and operationalize Apache Spark (and engines like Storm, Flink, and TensorFlow) based applications in the cloud 10x faster using an intuitive drag-and-drop interface, an exhaustive set of pre-built operators, full application lifecycle support, and one-click options for on-premise and cloud deployments.

  • Build data applications up to 10x faster
  • Boost performance by 4x using the same infrastructure
  • Have your existing team work at 3x efficiency
  • Process 1Mn+ events per second – both on-premise and in the cloud

Key features

  • Unified batch and streaming data processing: Ingest and blend data at scale from any data source – batch or streaming
  • Click + code: Use an exhaustive set of pre-integrated drag-and-drop operators in an intuitive visual interface, or introduce custom logic in the language of your choice (Java, Scala, or Python)
  • End-to-end data processing: Supports data ingestion, data preparation and processing, analytics, data science and machine learning, action triggers, data visualization, and data storage
  • Data flow lifecycle management: Build applications end-to-end with support for the entire application delivery lifecycle; design, build, test, debug, deploy, monitor, and manage
  • Open source flexibility: Work with the power and flexibility of best-of-breed open source technologies integrated into a high-performance, scalable, and reliable enterprise-grade platform
  • Multi and hybrid cloud support: Build your applications and pipelines and host them on any cloud provider of your choice or host over a hybrid environment

To learn more, download the Solution Brief.

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Intelligent and automated transformation of your enterprise data warehouse to Snowflake — The cloud data platform

Intelligent and automated transformation of your enterprise data warehouse to Snowflake — The cloud data platform

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.

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Intelligent and automated transformation of SAS analytic workloads to a cloud-native stack or Spark

Intelligent and automated transformation of SAS analytic workloads to a cloud-native stack or Spark

Is your organization looking to reduce its dependence on the SAS platform?

Offloading your SAS workloads to a distributed processing paradigm will help you cut costs while simultaneously establishing a vendor agnostic, easily scalable analytics platform. But the manual migration process can be long, complicated, and risky.

What if there’s a solution to automate and accelerate your transition from SAS to the cloud?

Read this solution brief to find out how you can avoid the tedious manual migration process by adopting an automated, accelerated approach.

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Automatically transform Netezza to big data or cloud

Automatically transform Netezza to big data or cloud

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.

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Building a Single Source of Truth across the Enterprise – An Integrated Solution

Building a Single Source of Truth across the Enterprise – An Integrated Solution

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:

  • Move to a cloud or an on-premise big data warehouse using automation
  • Build an enterprise BI consumption layer
  • Deliver self-service and interactive insights on big data

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