Modern Data Architecture: How It All Works

Instead of just creating a data lake, an organization can utilize modern data architecture to incorporate a data warehouse/data lake. This permits you to transfer data across different platforms and apps easily. Modern data architecture enables organizations to manage and collect data efficiently. It eliminates the need for them to take a one-size-fits-all approach to analytics. Amazon Web Services (AWS) provides customers with a modern data architecture that allows building and managing data lakes, securing and managing their systems, and scaling them at a low cost. With a wide assortment of data services and a modern security and governance framework, they can easily share data across their organizations.

Scalable Data Lakes

Integrate various analytics & data approaches by handling the required scale, agility, and flexibility.

Purpose-Built Analytics Services

Optimize performance, price, and scale by rapidly extracting meaningful data insights.

Seamless Data Movement

Focus solely on your app, while AWS services will help to move your data seamlessly.

Unified Governance

Efficiently manage your governance policies to fulfill industry and geography-specific constraints easily.

Performant and Cost-Effective

Get the most out of your solution while also preventing unnecessary budget devastations.

Scalable data lakes

Run your data lakes on AWS and join the cohort of those who always reach success.

  • Amazon Simple Storage Service (S3)
    Regardless of the size of your organization, Amazon S3 allows you to keep and protect data while ensuring market-leading scalability and efficient performance.
  • AWS Lake Formation
    Decide what access and security policies you need to involve and set up a centralized, curated, and secured repository in a fast and easy manner.
  • Amazon Athena
    With this out-of-the-box query service, you can crawl data sources, build metadata repositories, and populate your Catalog with unique definitions.
  • AWS Glue
    AWS Glue enables you to shorten the time-to-market period by analyzing your crucial data insights in minutes instead of months.

Purpose-Built Analytics Services

With such a wide array of purpose-built analytics services offered by AWS, you will definitely find what suits you best.

  • Amazon Athena
    With a simple query service, you can easily build metadata repositories and browse data sources. You can also customize the definitions of your catalog.
  • Amazon EMR
    Processing vast amounts of data has never been easier. Perform it quickly and cost-efficiently with this superb cloud big data platform.
  • Amazon Kinesis
    Get real-time streaming data analytics and transform them into meaningful insights to grow your business. No delays, only timely analytics processing.
  • Amazon OpenSearch Service
    Designed for deploying, operating, and scaling clusters, this analytics engine provides multiple analysis options, including log analytics, real-time app monitoring, and clickstream examination.
  • Amazon Redshift
    Being one of the most popular cloud data warehouses, Amazon Redshift utilizes SQL to explore structured and semi-structured data while ensuring the best price performance at any scale.

Unified Data Access

As the amount of data in your data lakes and purpose-built data stores constantly extends, moving a piece of that data from one store to another is pivotal.

  • AWS Glue
    AWS Glue enables you to shorten the time-to-market period by analyzing your crucial data insights in minutes instead of months.
  • Amazon Kinesis Data Firehose
    Whether you need to capture, transform, or deliver streaming data to data lakes, data stores, or analytics services, this all-in-one service will flawlessly fulfill your goals.

Unified Governance

One of the most critical factors that sets a modern data architecture apart from a traditional one is its ability to allow customers to manage and access their data.

  • AWS Lake Formation
    Designed to store all your data in its original and ready-for-analysis form, this service makes it easy to set up and manage a secure data lake in just a couple of days.

Performant and Cost-Effective

Amazon Web Services (AWS) is committed to providing the lowest cost possible for all analytics services.

  • Amazon Simple Storage Service (S3)
    Amazon S3 is an object storage service that enables customers to store and protect their data in a secure and scalable manner. It's ideal for both small and medium-sized businesses as well as large organizations.
  • Amazon EC2
    Amazon EC2 eliminates the need for hardware investment in order to develop and deploy applications.
  • Amazon EMR
    With Amazon Elastic MapReduce, you can quickly process large amounts of data as it allows you to quickly build and deploy applications.

clients’ Success stories

MULTI STAGE DATA PIPELINE

Being a powerful player in the wellness & fitness niche, Naring Health handles multiple diet-related services under one roof. On the one hand, they evaluate DNA, microbiome, and metabolic reaction to particular meals or dietary practices to define a sufficient eating program to prevent or treat disease.

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AWS NATIVE KUBERNETES SOLUTION

As one of the most influential humanitarian organizations, Adra specializes in managing diversified services, each of which is intended to help individuals, communities, and society as a whole. Such a charity-oriented mission undeniably requires a robust technical foundation.

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A HIGHLY AVAILABLE MICROSERVICE ARCHITECTURE

In the modern business ecosystem, it is essential to constantly improve your services in order to engage potential clients and keep pace with the competitors. Growing means consistently examining your current infrastructure for weak areas and considering whether what you have in place is not only meeting the basic needs of your company today but also setting you up for triumph in the increasingly cloud-focused future.

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INFRASTRUCTURE & DEVOPS SERVICES FOR FINTECH PRODUCT

The client experienced the need to automate the deployment process of microservices and simplify the release process. One of the requirements was to migrate Docker containers to AWS ECS and move existing infrastructure to Terraform.

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CLOUD & DEVOPS SERVICES FOR CLOUD NATIVE PRODUCT

The client had a manual multi-environment infrastructure deployment аnd no continuous integration & continuous deployment automation. That significantly impacted the speed of product development, release, and delivery cadence of new application versions in general. Besides, it required a considerable part of the development team capacity to process it manually.

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CLOUD & DEVOPS SERVICES FOR REAL ESTATE PRODUCT

The client faced the need to automate multi-environment continuous integration and deployment process of microservices, move the front-end part to CDN as well as deploy multi-environment infrastructure as a code.

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SERVERLESS DATA & ML PIPELINES

The client had high costs for development, deployment, and, most importantly, operation of the data platform including Data Lake, Ingestion, and ML Pipelines. The pipelines were mostly running in EC2 instances, which led to the increased cost of operations and required a significant amount of time to deploy and test the pipelines in lower environments.

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SERVERLESS DEPLOYMENT AUTOMATION

The client came with a request to automate and unify the deployment process of serverless applications on AWS Lambda. Having manual deployments before, the customer was facing inconveniences and difficulties, including non-uniform environment setup (versions of Serverless, Python, Node, and so on were inconsistent) and inability to control the environment changes in one place.

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DATA SCIENCE INFRASTRUCTURE

The client needed to strengthen collaboration within the data scientists team by moving research capabilities into cloud workloads. Besides, they wanted to automate and unify the deployment process of AWS resources. That, in turn, would decrease the time and effort required for a team of data scientists to build and test their models.

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CI/CD FOR MOBILE CROSS PLATFORM APPLICATION

Initially, the client’s development team performed continuous integration and continuous deployment processes manually. Consequently, it was time- and effort-consuming to build cross-platform mobile applications. Besides, they used the legacy tools stack – that doesn’t have built-in mobile-specific continuous integration and deployment capabilities.

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SERHII YELCHENKO

Delivery Director

We are cloud native company who visions cloud computing as the home for tech products. Our team of top-notch engineers specialize in Cloud solutions, we develop scalable cloud native applications, provide DevOps services which facilitate innovations and allow release products faster, build reliable and secure cloud infrastructure for our clients from the US and Europe.

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