AWS Smart Analytics Implementation

Unlock the value of your data and accelerate time to insights with AWS Smart Analytics implementation powered by purpose-built AWS services.

In today’s world, organizations are realizing the true value of their data, companies are using data analytics to predict client’s behavior, uncover trends, prevent defects, and optimize processes. But with the vast of type of data sources, organizations need tools to analyze data coming not only from enterprise applications, but also from external parties, websites, social media, emails, maps, logs, and more. These new data sources bring new challenges: where to store these large volumes of data, how to compute and process the data faster and what tools to use to analyze data in an efficient and cost-effective way?

Why Implement AWS Smart Analytics?

AWS Smart Analytical services is a series of purpose-built AWS services that enable organizations to turn data into actionable insights in a secure, scalable, and cost-efficient way. Adastra masters AWS services such as Amazon Athena, Amazon S3, Amazon OpenSearch, Amazon Redshift, Amazon QuickSight, and more to help industry leading companies accelerate to insights and drive business innovation.

Make Informed Decisions

Business can use AWS Smart Analytics to understand trends and anticipate changes on their business model. This knowledge can be used to drive investments and to get better prepared for those changes instead of reacting to last minute situations. After collecting and analyzing data, business can validate a course of action before committing to it.

Optimize Costs

Cost optimization is one the primary focus of most organizations. Companies can reduce costs while adding value to their product and services. AWS Smart Analytics provide the insights identify which costs to reduce or eliminate without compromising growth.

Mitigate Risks

Business can use AWS Smart Analytics to understand trends and anticipate changes on their business model. This knowledge can be used to drive investments and to get better prepared for those changes instead of reacting to last minute situations. After collecting and analyzing data, business can validate a course of action before committing to it.

Prevent Outages

Using AWS Smart Analytics, organizations can use a predictive device health monitoring to create an optimized preventive maintenance schedule. Imagine having a schedule for maintenance just on time before a machine or a device requires it. These models can help reducing cost, enhancing workplace safety, and improving customer experience.

Enhance Security

Data security is a big concern for today’s organizations, institutions, and governments which are facing numerous data security threats. With AWS Smart Analytics services, you can analyze logs, identify data vulnerabilities, prevent threats, and minimize the risk of potential data losses due cyber-attacks.

Personalize Customer Experience

AWS Smart Analytics services help organizations to collect, integrate and analyze large amounts of customer data received from multiple sources and react fast to customer changing behavior. That data could include location, interaction, sentiment, and other factors of the client’s interaction with their products and service.

Modernize your Data Analytics process with AWS Smart Analytics

You can easily collect, transform, and integrate large amounts of data using the AWS Smart Analytics services. After data is properly organized for consumption, users can easily utilize it to visualize insights with just a few clicks or use it for advance analytics and machine learning models.

AWS Services that Help Us Master AWS Smart Analytics

Amazon Athena

A serverless and interactive query service that makes it easy to analyze data directly in Amazon Simple Storage Service (Amazon S3) using standard SQL.

Amazon OpenSearch

A fully open-source search and analytics engine for use cases such as log analytics, real-time application monitoring, and clickstream analysis.

Amazon Redshift

A fast, fully managed, petabyte-scale data warehouse that makes it simple and cost-effective to analyze all your data using your existing BI tools.

Amazon QuickSight

A cloud-scale business intelligence (BI) service that you can use to deliver easy-to-understand insights to the people who you work with, wherever they are.

Adastra’s Smart Analytics Craftsmanship

Discover, prepare, and combine data for analytics, machine learning, and application development with ease.
Modernize your data warehouse and allow it to cope easily with unpredictable workloads, while not affecting the time-to-insights ratio.
Embrace scalable self-service business intelligence that turn your data into actionable insights.

Approach to AWS Smart Analytics Implementation

Adastra can assist with your analytical use cases, our methodology covers the discovery, design, and implementation phases. When it comes to the stages of the analytical journey (data movement, data storage, data manipulation, and data consumptions), the Adastra team has the expertise to recommend a modern architecture design for a future proof end to end solution.

We identify all stakeholders and conduct a series of exploratory workshops to get acquainted with the organization’s current technological platform, data strategy and long-term plans, including key business objectives and use cases that should be implemented.

We join forces to create an AWS Smart Analytics architecture and implementation plan that outlines the required resources, skillset, and any necessary integration to your applications. The architectural design artifacts include detailed description of capabilities, a clear definition of roles and responsibilities as well as cost estimation for the AWS services required to implement the solution.

Our experienced team of AWS professionals execute the tasks to implement the processes and services described on the architectural design following the AWS Well-Architected framework. Our goal is to implement a secure, high-performing, resilient, and efficient AWS Smart Analytics solution which enables users to obtain insights through a fast, easy to use, and collaborative cloud platform.

We produce all the documentation required by your team to fully operate and use the end-to-end solution, including a runbook. We perform transfer knowledge sessions where will answer any questions regarding the implemented solution.

Success Story

DWH Modernization on AWS 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.


unique data quality issues have been resolved


reports and dashboards have been migrated


increase in reports accuracy

“The implementation of the AWS Cloud Analytics Platform powered complex insights into our business in an automated fashion. This eliminated the need of manual data manipulations and allowed all business users to focus on our main mission – offer high-quality, affordable healthcare and deliver integrated medical services with compassion and care.”

Chris Smith | VP Digital Health, Skylight Health Group

Featured Resources

Frequently Asked Questions


  • Identify all stakeholders.
  • Conduct a series of exploratory workshops to get acquainted with the end-to-end environment – identify data volumes, producers, consumers, analytics requirements, etc.
  • Create a classification of the teams and processes which would benefit from the analytical services.
  • Identify objectives and business goals of the solution.

Design and plan

  • Create a high-level design of the solution, making sure it integrates well with existing environments, while taking into consideration the possibility of future architectural changes.
  • Create an end-to-end implementation plan, including scope, timelines, milestones, and deliverables.
  • Define the data ingestion, data storage and data transformation strategy for each data source system.


  • If this is your first cloud project – our team will help you establish all necessary, cloud-based infrastructure and security mechanisms.
  • In case of migration from an on-prem system – perform shadow test to identify the right size and configuration of the analytical services, the goal is to get the same or better performance at a lower cost, compared to your on-prem solution.
    Implement data pipelines to ingest data from the identified sources.
  • Implement or migrate data transformation and analytics workloads.
  • Configure CI/CD pipelines to automate, testing and deployment.
  • Create the reports and visualizations ready to consume


  • Deliver detailed technical documentation which will allow your team to operate efficiently the new environment.
  • Conduct knowledge transfer and training sessions, making sure all technical and business users are well-acquainted with the delivered solution, its features, and capabilities.

Start Modernizing your Data Analytics process with AWS Smart Analytics