Data Engineering

Large volumes of data turned into valuable insights.

How can we help?

The Success of your Data venture is as good as the information it engages with. Yet, as organizations gather conflictingly arranged data from various sources and in colossal sums (big data), the chances of this data presenting some issue that will harm your Machine Learning efforts increase.

  • Big Data Engineers are the ones liable for all big data examination (data analytics). They handle realities that data scientists and experts utilize later to transform into artificial intelligence models, discover and oversee data sources, and build up your association’s data solutions and management.
  • Organized data is valuable information, so overseeing tremendous volumes of data begins with planning and making a Data Warehouse or modernizing your current DWH to fit your innovative principles and scale, increment execution, and decrease costs.
  • To help your people effectively access the data they need, we make data lakes that will sustain your information driven endeavours. What’s more, to handle and process this data we construct applications utilising technologies like Hadoop or Spark to deal with data streams progressively.
  • Our information engineers will discover, arrange, and store large data for your task, either as a piece of your IT department or data driven solutions delivery.

How we work?

What we do in Data Engineering

Concept Map

Architecture

We help you asses your current architecture around Data to identify lakes, DWHs and sources.

Scrumban

Data cleanup

We help you with Data cleansing to make data usable for modelling.

Development

Tools selection

We will guide you in selecting the appropriate open source tech, big data analytics tools and solutions for your product.

Task Analysis

Infrastructure

We help you make the right choice for your infrastructure: AWS (amazon web services, Microsoft azure, google cloud platform, SAP, IBM, Terradata and more).

Let’s talk

Got a project?

Madiff provide Sprint as a service mode to cater to the needs of fast-growing companies in need of scaling their tech product to meet the needs of their customers, investors, and strategic goals!

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