Data Engineering

Make your business transparent and discover valuable insights out of data. We provide Microsoft Azure Consulting Services, and as professionals with BI expertise, we build reporting solutions based on the Power BI Insights Delivery Dashboard for various industries.

Why customers choose Akveo:

We combine BI technical expertise with business domain prowess.

We drive cost-effective solutions, designed to match your goals, timeline, and budget.

We are experts in data engineering.

We have a proven track record of successfully delivered projects.

What we deliver

Data Platform Design Icon

Data Platform Design

Let's build a state-of-the-art data and analytics platform design that your users would love.
Database Development Icon

Database Development

The use of custom database development best practises makes it possible to deliver maximum efficiency and generate more value.
Data Warehousing Icon

Data Warehousing

Our cross-platform team will assist you in storing data regardless of your business requirements' complexity.
Data Warehousing Icon

Business Intelligence

Our experience in implementing BI solutions will help you confidently initiate your projects.
IoT real time analytics, Big Data Icon

IoT real time analytics, Big Data

We offer Big Data analytics and cutting-edge business intelligence tools to meet the needs of your customers.
Web Scraping Icon

Web Scraping

We can extract data from any website to identify and store integral information for future business use.
ETL/ELT Development Iocn

ETL/ELT Development

We can assist you with the development and tech support of lightweight, flexible, and transparent ETL systems for extracting all important data from your sources.
Reporting and data visualization Icon

Reporting and data visualization

Let's overcome any data visualization challenges, be it health checking and maintaining your current data visualization solution, or developing a new one from scratch.
Let's discuss your challenge >

Engagement models

Akveo Icon Time
Time and Material

The Time and Material approach provides a great deal of flexibility and suits companies involved in complex and long-term projects. Besides, ongoing projects at the testing or bug fixing stage or projects that require maintenance are also a good fit for the T&M model.

Before starting the project, we discuss the specifics and choose the optimal project length and timeframe. We provide an accurate quote and carefully stick to it during the development phase.

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Sketchy roadmap planning
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Flexible workflow
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High control requirements
Dedicated Team

This approach best works for enterprise-level projects. A dedicated team is fully focused on the IT solution, while the client controls the workflow and can focus on high-level tasks. Depending on the project’s complexity, we build the team that suits best a certain project.

During the development phase, you get transparent reports on delivered features and project progress. If needed, we can discuss a monthly budget limit.

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High control management
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Adjustable workflow
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Full transparency
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Flexible roadmap
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Fixed-Price

The fixed-price model is suitable for startups and projects with the limited project scope. First, we estimate the timeframe and budget required to deliver an MVP and then handle all the managerial tasks.

The price is usually based on a specified amount of work and cannot be changed once the contract is signed. Before we start the project, the discovery phase to develop clear requirements may be required.

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Detailed specifications
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Fixed timeline and budget frames
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Short-term projects
Time Icon
Time and Material

The Time and Material approach provides a great deal of flexibility and suits companies involved in complex and long-term projects. Besides, ongoing projects at the testing or bug fixing stage or projects that require maintenance are also a good fit for the T&M model.

Before starting the project, we discuss the specifics and choose the optimal project length and timeframe. We provide an accurate quote and carefully stick to it during the development phase.

Icon white
Sketchy roadmap planning
White point icon
Flexible workflow
Star icon
High control requirements
Dedicated Team

This approach best works for enterprise-level projects. A dedicated team is fully focused on the IT solution, while the client controls the workflow and can focus on high-level tasks. Depending on the project’s complexity, we build the team that suits best a certain project.

During the development phase, you get transparent reports on delivered features and project progress. If needed, we can discuss a monthly budget limit.

Star icon
High control management
White point icon
Adjustable workflow
Icon
Full transparency
Icon
Flexible roadmap
Coins Icon
Fixed-Price

The fixed-price model is suitable for startups and projects with the limited project scope. First, we estimate the timeframe and budget required to deliver an MVP and then handle all the managerial tasks.

The price is usually based on a specified amount of work and cannot be changed once the contract is signed. Before we start the project, the discovery phase to develop clear requirements may be required.

Icon
Detailed specifications
Icon
Fixed timeline and budget frames
Icon
Short-term projects

Technology stack:

Amazon Redshift
Amazon Redshift
Microsoft Flow
Microsoft Flow
Stream Analytics
Stream Analytics
Azure Data Factory
Azure Data Factory
Azure SQL
Azure SQL
Oracle DB
Oracle DB
Tableau
Tableau
MySQL
MySQL
Snowflake
Snowflake
Perl
Perl
Databricks
Databricks
Spotfire
Spotfire
Power BI
Power BI
Python
Python
Azure
Azure

What our customers say

Amy Curran, Velum Management

How We Built iOS, Android, and Web Apps for a Startup for the Price of One

Our business has expanded thanks to Akveo’s high-end services! Their contribution has exceeded our initial requirements. Being solution-oriented, Akveo's team establishes strong partnership relations to bring their clients tangible benefits. They always suggest innovative solutions, and remain open to any discussion.

Amy Curran

Principal Consultant, Velum Management

Key features our projects deliver

Contact us
1

Fully scalable data driven solutions that provide manufacturers with the production process insights to monitor, predict, and make the right decisions  at the right time

2

Modern cloud-based technology stack (Azure, AWS) that allows to save resources on maintenance

3

Automated process of gathering data

4

Real-time asset monitoring and immediate failure notifications

5

Detection of data anomalies and hints for fixing it

* Based on 100+ projects we delivered

Our expertise in implementing Data Engineering Solutions

How we did refactoring of an inefficient reporting solution

Customer

US-based developer of a messenger platform.

Key Result

We’ve got a simple, straightforward and well-documented solution that can scale based on the current workload. This is cost effective as it only charges during processing and not when idle.

Challenges

The client had a reporting system for the messenger, but it was implemented without proper engineering approach:

  • each feature was implemented with no regard to the whole solution, cause there was no  thorough architecture;
  • it was impossible to find where specific feature had been implemented, as a whole bunch of tools and technologies were used: mix of cloud/on-premise, mix of languages (Python, Perl, sql, bash);
  • the documentation was missing.

Solution

Our team started from analyzing and documenting the existing solution and requests for improvements. The second step was to design a new solution's architecture and suggest a set of software tools which would cover required features, would be able to scale and cost-effective.

From scratch we implemented Data Warehouse, ETL process, Reports and Customer Portal. As well we enabled direct access to data in multi tenant Data Warehouse.

Technical Details

  • Data Warehouse size – 400Gb
  • ETL runs 1 time/day processing 1Gb
  • 150 tenants in single Data Warehouse
  • 3000 reports being generated and emailed daily

Toolset

  •  Snowflake for Data Warehouse
  •  Apache Airflow for ETL
  • AWS EC2 for hosting Airflow and other tools
  •  AWS RDS for supporting relational database
  •  AWS S3 for File Staging and Storage for Generated Reports
  •  AWS SES for reports delivery via email
  • StimulSoft for reports generation

Team Composition:

  • Project Manager,
  • Data Architect, 
  • 4 Developers,
  • 1 DevOps, 
  • 1 QA, 
  • 1 BA

Key Achievements:

We’ve got a simple, straightforward and well-documented solution that can scale based on the current workload. This is cost effective as it only charges during processing and not when idle.

 Our team successfully:

- analyzed and documented an old solution and requirements for the improvements;

- prepared a new solution proposal which included architecture, description of the mail features and suggested set of software tools;

- implemented the project and made a transition from the old solution to the new one.

How we implemented electronic car parts catalogs

Customer

Supplier of technology solutions in the automotive industry.

Key Result

We successfully implemented Catalogs for 5 manufacturers, which helped the customer to save approximately $100 000 per on subscriptions.

Challenges

For years the client has been acquiring electronic parts catalogs spending $5000-50000$ per month for each catalog. Our team accepted a challenge to design and implement a solution which would generate and update the catalogs for 5 parts manufacturers from source data.

Solution

 Each manufacturer has their source data in their own format - text files, xml, excel, databases (.MDF) and even EBCDIC - the format used since the 50s on IBM mainframes.

The goal was to build ETL pipelines which would transform diverse source data and enable a single set of APIs to query all catalogs.

On Stage raw data is imported into MS SQL Database, cleaned and validated. Stage only contains a set of data being processed (it is cleared at the beginning of each ETL run).

Data Warehouse is a permanent data storage with all data sets integrated and normalized (not a canonical data warehouse).

Deliverable Database contains data with applied business rules and transformations required for enabling access by API. APIs are implemented as SQL procedures.

Technical Details

  • ETL runs 1 time/month for each manufacturer, processing time 1-8 hours
  • Largest Deliverable Database is 150Gb
  • APIs response time is 300ms (required a lot of optimization)
  • TeamCity is configured to run integrity checks, auto tests and build catalogs on full data sets
  • Auto tests cover ETL and all APIs, implemented on SpecFlow

Toolset

  •  On-premise Microsoft SQL Server for all databases
  •  Microsoft SSIS for ETL
  • TeamCity for Continuous Integration
  • SpecFlow for auto tests

Project Duration: 2.5 years

Team Composition:

  • Project Manager,
  • 6 Developers, 
  • 2 QA,
  • 1 BA,

Key Achievements:

  • Customer saves approximately $100 000 per on subscriptions;
  • High quality of catalogs which saves resources on maintenance;
  • We enabled full access to catalogs and ability to update catalogs at any time.

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