AWS Redshift migration services by Adastra.

AWS Redshift Migration Services

Migrate your enterprise data warehouse to Amazon Redshift to sustainably improve query and data load performance, increase scalability, and save costs.

AWS Redshift migration services by Adastra.
Overview

Whether you are beginning your analytics journey, looking to extend your existing capabilities for broader reporting and insights or have a pre-existing solution but are realizing your need for greater flexibility or scale, AWS Redshift offers your enterprise a high caliber platform.

From Adastra’s 20+ year history, we have extensive experience in implementing and modernizing legacy systems. We will leverage best practices and accelerators to implement Redshift, ensuring that you achieve fast-tracked delivery and value from your analytics engine.

The success of modern businesses relies on the prioritization of data-driven decision-making through results-oriented analytics.  At their core is a modern, scalable, and cloud-based platform tailored to deliver fast value-add insights. Whether you are beginning your analytics journey, looking to extend your existing capabilities for broader reporting and insights or have a pre-existing solution but are realizing your need for greater flexibility or scale, Redshift offers your enterprise a high caliber platform.

Why Perform AWS Redshift Migration?

Experience lightning-fast query performance, effortless scalability, and optimized cost management. Leverage seamless integration with AWS services, advanced analytics capabilities, robust security, and a managed service approach.

Cost Efficiency

Allows for scale and flexibility in the scope of your data warehouse. Costs start with as little as 25c per minute.

Easy Management

Automated backups, patching, recovery, computing infrastructure, load balancing, planning, scheduling and execution of S3 queries.

Advanced Analytics

Ability to analyze structured or semi-structured data in Amazon S3 with Redshift Spectrum.

Virtually Limitless Flexibility

Scales to hold petabytes of data and enables querying of exabytes from your data lake. Allows advanced optimization to further optimize performance up to 10x.

Security and Encryption

Industry-leading security and encryption techniques to keep your data safe both at rest and in transit. The platform is certified to meet all common regulations.

AWS Redshift Migration Use Cases

An EDW can be improved but at times, it is simply more strategic to rebuild and rearchitect the solution, as both technology, business needs, and priorities have changed too much. A migration to the cloud, combined with a modern architecture including Amazon S3 and Amazon Redshift should be part of the new data landscape.

Data Estate Modernization

As part of a modern architecture, organizations inevitably implement a Data Lake to support their analytical needs, but this is just the beginning of the journey. Typical organizations will need a robust database to allow the democratization of analyses to a large number of users across the enterprise, handling various use cases and complexity. Amazon Redshift, working in tandem with Redshift Spectrum and Amazon S3 enable a Lake House Architecture, combining the best of the Data Warehouse and Data Lake platforms.

Database Refactoring of Legacy EDW

Early adopters of Data Warehouse have implemented solutions like Teradata, Oracle and Netezza, which could handle large volumes of data but at a high price point. Later implementations of SQL Server had a lower price point but all of them were limited in their ability to support analytics in a true Big Data world, thus imposing constraints. Redshift has a lower price point than all those options, by orders of magnitude at times. More importantly, it does not suffer from the same limitations and will not constrain an organization from any use cases it is considering.

Re-architecture of Legacy EDW

Despite the costs associated with early Data Warehouses, some organizations made good use of them and still had an upper hand amongst their competitors. Over time, standards and architecture evolve drastically increasing the costs required to maintain the older platform. The business needs to evolve even more drastically and often to a point when the EDW fails to keep up.

Our Approach to AWS Redshift Migration

Discovery Session

Adastra will start by outlining the advantages of AWS Redshift, describe a best practice architecture and typical use cases.

We will then tailor the discussion to your organization. Adastra will lead you through an analytic discovery workshop with your organization, to determine how Amazon Redshift can specifically provide value. We will learn about your organization’s current analytics needs to help envision how Redshift will benefit your organization and identify viable use cases to showcase Redshift’s value and impact.

Adastra and AWS will hold a one-day session where we review the AWS Redshift capabilities in more detail, as well as allow for hands-on experience that will validate first-hand the fit for your organization.

This will help ensure the customer’s active participation in the pilot as well as ensure that they can remain self-reliant after the initial POC.

We will implement foundational AWS Redshift services aligned to your technical governance standards, to host your pilot solution. Adastra will provision an environment and tailor the type of nodes, additional concurrency nodes, queues, etc. to your organization. In doing so, we will show you the console and explain how to also manage and monitor the platform.

Upon identifying some datasets, Adastra can convert an existing data model or create a brand new one and proceed to load all the data, with enough volume to enable performance tests. Should you not have a Data Lake yet to hold the datasets, we can setup one for you and help you transfer the datasets. In both cases, we will also set roles and relevant access controls.

Once data is loaded, we can help you with more advanced features such as stored procedures and materialized views. If the use case calls for it, we can also leverage AWS Redshift Spectrum to query data from the Data Lake in an integrated fashion.

Finally, we will automate all the environment provisioning using CloudFormation to enable its automation and repeatability.

Adastra will review the outcomes of the POC and the expected impact on the organization. We will also suggest next steps, with a viable roadmap forward to scale the implementation across the organization.

Our Success Stories with AWS Redshift

Frequently Asked Questions

AWS Redshift is a fully managed, petabyte-scale data warehousing service in the cloud. It is designed to handle large datasets and perform high-performance analytics for data-driven decision-making.

AWS Redshift achieves fast query performance through a combination of columnar storage, parallel query execution, and data compression techniques, which optimize data retrieval and processing.

AWS provides various options for data migration to Redshift, such as using the COPY command, AWS Database Migration Service (DMS), or leveraging partner tools for seamless data transfer.

AWS Redshift offers seamless scalability through automatic distribution and parallel processing. It allows for adding or removing nodes, scaling up or down, to accommodate varying data volumes and performance requirements.

Redshift Spectrum is a feature that enables you to run queries directly against data stored in Amazon S3. It extends Redshift’s querying capabilities to analyze vast amounts of data without loading it into the cluster.

AWS Redshift follows a pay-as-you-go pricing model based on factors such as the number and type of nodes, storage usage, and data transfer. Detailed pricing information is available on the AWS website.

Redshift provides robust security features including data encryption at rest and in transit, VPC integration, fine-grained access controls, and integration with AWS Identity and Access Management (IAM) for user management.

Yes, Redshift seamlessly integrates with other AWS services such as S3, Glue, Athena, QuickSight, and more, enabling data ingestion, transformation, and visualization within the AWS ecosystem.

While AWS Redshift is primarily optimized for batch processing and data warehousing, it can support near real-time analytics by using tools like AWS Lambda, Kinesis, or data streaming platforms for data ingestion.

Modernize Your Data Warehouse with AWS Redshift Migration