AWS Data Warehouse Modernization

Modernize your data warehouse and allow it to cope easily with unpredictable workloads, while not affecting the time-to-insights ratio.

Why Implement an AWS Data Warehouse?

The Data Warehouse landscape is constantly being changed by emerging technologies, which usually bring a cost advantage with them. More than ever before, organizations now need solutions to not only answer their analytics needs, but also provide features and functionalities which will enable the generation of new value – and all that at much lower cost and much higher rate.

Performance

Get faster time-to-insight for all types of analytics workloads. Dynamically scale up to guarantee performance even with unpredictable demands and data volumes.

Cost

Lower total cost of ownership starting from $0.25 an hour.

Next-Generation Analytics

Create, train, and apply Machine Learning models on your Redshift data using only SQL and leveraging AWS Redshift ML feature.

Backup and Disaster Recovery

Redshift continuously creates backups of your data in AWS S3 and asynchronously creates copies of it in different regions for Disaster Recovery.

Out-of-the-box Security

Secure all workloads leveraging Redshift’s end-to-end encryption and integration with AWS Key Management Service.

Flexibility

Create a data mesh and combine your structured data with any semi-structured or unstructured data in your Data Lake.

AWS Data Warehouse Craftsmanship

With vast experience in architecting data warehouse (DWH) and cloud solutions, Adastra can help you implement a modern data warehouse in the cloud. As an Advanced AWS partner, we deliver secure and cost-effective solutions, which help your business grow, based on data-driven decision-making.

Strategy Alignment and Roadmap

Adastra will help identify your data strategy, cloud maturity, environment, and analytics requirements. Based on our findings, we will design the cloud data warehouse and help you build a roadmap that outlines how it can serve an increasing number of users across your organization.

DWH Modernization

Our AWS team will design a solid and scalable solution for your cloud data warehouse, based on global best practices and choosing the right AWS services for the job. All your source data will be integrated and loaded into the cloud data warehouse with all jobs fully automated and orchestrated in order to achieve minimum processing times.

Knowledge Transfer

We make sure your team is fully capable of managing the implemented cloud data warehouse and is comfortable working with it. Optionally, you can benefit from Adastra’s managed services where we will run and update the solution for you, leaving you to focus on other business priorities.

Approach to AWS Data Warehouse Implementation

  • Identify all stakeholders
  • Conduct a series of exploratory workshops to get acquainted with your organization’s data strategy and long-term plans
  • Capture all source systems characteristics and interface specifications
  • Gather all reporting requirements from your team

  • Create a high-level design of the solution, making sure it integrates well with the existing environment, while taking into consideration the possibility of future cloud migrations
  • Create an end-to-end implementation plan, defining scope, timelines, milestones, and deliverables
  • Adastra can reuse and slightly adjust your available DWH model, or we can create a custom-tailored model which will take into consideration any limitations or inefficiencies with your current one
  • Optionally, if you plan to expand your activities in the cloud beyond the data lake, we can help you create a roadmap

  • Our team will establish all necessary, cloud-based infrastructure and security mechanisms
  • Implement data pipelines to profile and ingest data from any identified source
  • Configure CI/CD pipelines to automate to a great extent testing and deployment
  • Build the visualization layer using either Amazon QuickSight or any other supported business intelligence tool

  • Adastra will deliver detailed technical documentation which will allow your team to independently run the cloud data warehouse
  • Conduct knowledge transfer and training sessions, making sure all technical and business users are well-acquainted with the delivered solution and reports
10x Greater Report Accuracy for AstraZeneca through DWH Modernization on AWS
Success Story

AWS Data Warehouse Modernization for AstraZeneca

AstraZeneca needed to implement a modernized platform that would create a single repository of trusted information, across their organization.

Adastra architected and implemented an enterprise Data Warehouse, leveraging Amazon Redshift to replace AstraZeneca’s on-premise Oracle and Business Objects solution, instilling a set of Governance best practices and accelerators to ensure trust and accuracy.

175

unique data quality issues have been resolved

200+

reports and dashboards have been migrated

1000%

increase in reports accuracy

“The level of cooperation between members of our organization and Adastra has always been outstanding. The implementation of the AWS Cloud Analytics Platform powered complex insights into our business in an automated fashion.”

Chris Smith | VP Digital Health, Skylight Health Group

Success Stories

Cloud Data Warehouse FAQ

A data warehouse is a central repository of information which is analyzed to support the decision-making processes in your organization. Data from various sources like transactional systems, relational databases, etc. flow into the data warehouse and is used by business analysts, data analysts, data engineers, and decisionmakers to satisfy various requirements. In most cases, data in the data warehouse is accessed through various business intelligence tools, SQL clients and other analytics applications. A data warehouse typically provides the following benefits:

  • Supports the decision-making process
  • Integrates and consolidate data from various sources
  • Measures the quality, accuracy, and consistency of data
  • Provides analysis on historical data
  • Separates the analytical workloads from the operational workloads on the transactional systems

The advantages of cloud services vs. on-premises infrastructure and solutions are numerous. As a starter, you avoid huge capital expenditures and the risk that you under or overprovision the necessary hardware. Also, there is no need to adjust your organizational structure just to make sure that you have teams who can manage the required on-prem hardware, software, networking, and security. 

With AWS services you can cut capital expenditures and replace them with much more effective and reduced operational expenditures as you pay only for what you use. Your solutions can scale both vertically and horizontally depending on the workload, in a matter of minutes. You can also take advantage of the shared responsibility model and fully managed services, where AWS-as-a-service provider will take care of security, maintenance, patching, and more, so your organization can focus on mission-critical activities.

Let’s Talk AWS Data Warehouse Modernization

Streaming data can easily be loaded into your data warehouse and used to provide insights in less than a minute. If you have a data lake within your environment, we combine any semi-structured or unstructured data from it with the structured data from you data warehouse and build the reports. Access deep, actionable insights across the entire organization.