Data Warehouse Modernization with AWS

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

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Success Story
Data Warehouse modernization with AWS by Adastra Bulgaria.

Mastering Data Analytics with AWS

By joining this event, you will have the exclusive opportunity to benefit from free AWS cloud consumption and Adastra’s consultancy on building a cloud data analytics use case.

When: June 9, 09:30 – 12:30 EEST

Venue: Hyatt Regency Sofia, Bulgaria

Online Platform: Zoom

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Why implement an AWS Cloud 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.

What we do to modernize your Data Warehouse

With vast experience in architecting data warehousе 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 well-informed decision.

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1

Strategy alignment and roadmap

Identify what are your data strategy, cloud maturity, environment, and analytics requirements. Based on the findings, we design the Cloud Data Warehouse solution that your business needs and help you build a roadmap that outlines how the Cloud Data Warehouse serves more and more users across your organization.

2

DWH Modernization

Our expert teams design a solid and scalable solution for your Cloud Data Warehouse, based on world’s best practices, and choosing the rights AWS services for the job. All your source data is integrated and loaded in the Cloud Data Warehouse, with all jobs fully automated and orchestrated in order to achieve minimum processing times.

3

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 run and evolve the solution for you.

Approach to Data Warehouse Modernization with AWS

  • Identify all stakeholders.
  • Conduct a series of exploratory workshops to get acquainted with the organization’s data strategy and long-term plans.
  • Capture all source systems characteristics and interface specifications.
  • Gather all reporting requirements from your teams.
  • 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.
  • Based on case – we can reuse and slightly adjust your available DWH model, or we can create a custom-tailored model which will take into consideration any limitation or inefficiencies you’ve had 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 AWS native QuickSights or any other supported BI tool.
  • Deliver detailed technical documentation which will allow your team to 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.

Modernize Your Data Warehouse now

Streaming data now can easily be loaded into your Data Warehouse and used to provide “less than a minute” insights. 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 you have always needed. As an outcome, you have much deeper actionable insights across the entire organization.

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10x Increase in Analytics Team Productivity with an AWS Data Lake Implementation

10x

more productive analytics team

0

manual effort needed to produce unified and consolidated reports

0

infrastructure maintenance needed

A North American Health group was struggling with consolidating their accounting reporting as the group consists of a number of companies and clinics each of them using different accounting software solutions. The group was also looking at a centralized repository for storing and reporting on their EMR data (Electronic Medical Records).

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FAQ

A Data Warehouse is a central repository of information which is analyzed to support the decision-making processes in your organizations. Data from various sources like transactional systems, relational databased, etc. flow into the Data Warehouse and is used by Business analysts, Data Analysts, Data Engineers, and decision makers to satisfy various requirements. In most cases, data in the Data Warehouse is accessed through various Business Intelligent tools, SQL clients and other analytics applications. A Data Warehouse typically provides the following benefits:

  • Support the decision-making process.
  • Integrate and consolidate data from various sources.
  • Measure the quality, accuracy, and consistency of data.
  • 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 would be 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, security, etc.

With AWS services you can cut the 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 workloads in a matter of minutes. Also, you can take advantage of the shared responsibility model and fully managed services, where AWS-as-a-service provider is taking care of a great deal of the things (security, maintenance, patching, etc.), so your organization can focus on mission critical activities.

Let’s modernize your Data Warehouse with AWS