Data Engineering Consulting Services

Data Engineering is at the foundation of any data-driven company

Sucessful AI projects

80+

Data Engineering Projects

5+

Projects in 7+ countries

7+

Trusted by governments, market leaders, and banks

What is Data Engineering?

Data Engineering is at the core of robust data-driven companies.

Data engineering is what makes it possible for companies to deal with large amounts of data and large AI models.

Data engineering enables companies to collect raw data, process it, store it, and deliver it in a scalable way.

It does so by providing a reliable data infrastructure that will be foundational for further data-driven initiatives, from business intelligence to the deployment of prediction models.

Data engineering performs the following operations:

  • the organization of automated data collection from various sources in a single centralized repository, commonly called a Single Source of Truth - this can be a Data Warehouse or a Data Lake, for example;

  • moving and storing information;

  • control and improvement of data quality,

  • and much more. 

Data engineering develops the necessary foundation for data science processing.

Our Data Engineering Services

Although thrilling, your journey with data engineering can be overwhelming.

Data engineering is a vast field. There is a lot to know, and it is easy to become perplexed about how to implement data engineering in your business.

On your journey through data engineering, you may need some direction from time to time. Our world-class data engineering experts can provide you with advice.

To accommodate your schedule and needs, we provide a range of monthly retainer alternatives.

The advantages to your company include:

  1. World-class experts. Get access to top-tier data engineering professionals. 

  2. You'll save time. Imagine saving months of effort with your data engineering efforts. Working with our team of professionals is like having a secret code to success in data engineering.

  3. You'll save money. You won't lose time and money with bad initiatives. There are no expensive consultation billable hours; all consulting retainers are fixed fees.

How it works

  1. Introduction. Let's begin with a 15-30 minute call to learn more about one another and see whether we're a good fit. Decision-makers and key people should be present during this inaugural call

  2. Onboarding. Let's attend to the admin work (agreements and payment). Our onboarding procedure is straightforward, with the aim of providing you with value soon.

  3. Choose a consulting retainer option. You may choose to meet with us once per week or many times per week, depending on your preferences.

  4. Kick-off call. We begin the engagement with a one-hour call to discuss your existing challenges and objectives.

  5. Regularly scheduled sessions. We will meet on a regular and predictable cadence. You will receive specialized data engineering guidance during our meeting that is applicable to your context.

Pricing

Consulting retainers are charged at a flat rate. This takes away the guess work of how much you’ll be charged.

All consulting retainers include:

  • Access to our experts between scheduled sessions.

  • Month-to-month billing

Are you prepared to begin?

Are you ready to take your company to a new level? 

By selecting the button below, you can get in touch with us to schedule your data architecture and road mapping session.

Big Data Solutions

Sometimes the massive volume or speed of both structured and unstructured data exceeds current processing capacity making it impossible to process using traditional database and software techniques, we call that Big Data.

Data Engineering is what makes processing this data possible.

 
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Data
Lakes

Store all your company data in it is natural form. Centralize and store all types of data generated by and for the company.

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Data
Warehouses

Prepare your data for reporting and analysis. Use a subject-oriented data warehouse to support management decisions.

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Large Scale
Modeling

Running models on big data isn't easy if you don't have the right tools or don't know how to use them.

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Data
Pipelines

Move data from one system to the other, applying the correct transformations and quality control.