Data Engineering Services & Solutions | Techmango

Techmango Offerings

Data Engineering Services

Data Pipeline Development

Designing and developing data pipelines to ingest, process, and transform data from various sources.

Data Integration

Integrating different data sources and systems to enable seamless data exchange across the organization.

Data Warehousing

Designing, building, and maintaining data warehouses to store data in a centralized repository, enabling faster data retrieval and analysis.

Data Modeling And Architecture

Defining the data model and architecture for the organization’s data, ensuring the data is structured and organized in a way that supports efficient processing and analysis.

Improving data quality

Techmango can help organizations improve the quality of their data, so they can make better decisions based on accurate and reliable data.

Why Techmango

Leading Data Engineering Services Company

In the modern data era, Techmango isn’t just a partner. We see ourselves as an extension of your team, contributing significantly to your company’s success. From day one, we fully integrate with your employees, staff, systems, and practices to identify problems, strategize and develop solutions, and actively work with you to enable your company’s growth.

8+
Domains
50+
Projects
2x
Delivery
10+
Cloud Migrations

Our Data Engineering Services Process

The term “data engineering” refers to a set of procedures that transform a substantial amount of data into a useful output that can be used by analysts, data scientists, machine learning engineers, and other professionals. The following stages make up an end-to-end workflow in most cases.

We are preferred partners for data engineering solutions by top branded companies across the globe.

Talk to Us

Case Studies

Data Engineering Services Experience

case_study_img

case study

Pricing Strategy

Business is directly impacted by fluctuating operating costs and it can be challenging to understand the impact of operating costs on profitability because expenses and revenues are often tracked in separate systems.

case_study_img

case study

Power BI Dashboards for IT Services

Our customer is a large IT Services company. Objective is to resolve the Operational difficulties of project management users group in tracking and reporting operational metrics which are crucial in ensuring revenue.

case_study_img

case study

Visitor Analytics for Retail using IoT

Solution is about analyzing demographic using the IoT sensor data from offline stores. Customers were looking for a scalable data platform that can be reused and extended for multiple customers and brands.

View All Case Studies

Our Industry
Expertise

Data engineering services involves the use of tools and techniques to analyze and interpret data in order to extract valuable insights and make informed business decisions. The applications of data analytics are vast and can be used in virtually any industry, from healthcare to finance to retail.

Get Started

Retail
Manufacturing
Real Estate
Finance
Logistics
IT Services
Sports
Health Care

Technical Stack

Data Engineering

Depending on the particular demands and requirements of the organisation, the datastack utilised for data engineering can vary significantly. The knowledge of Tech Mango will assist you in choosing the best solution for your requirements, one that can successfully handle massive volumes of data, deliver precise insights, and generate commercial value.

- AWS
- Azure
- Other Tools

Still not sure what to do ?

Join together with us we will be your extended ARM, we bring lot of valuable expertise, objectivity, efficiency, cost-effectiveness, and competitive advantage for organizations looking to leverage their data for better decision-making and business success.

Talk with us

Let’s have a discussion about how you can develop or modify your application.

business@techmango.net

Got a project in mind ?

Honoured with Awards

Frequently Asked Questions

How can we help you?

What is data engineering?

Data engineering involves the use of software engineering principles to design, build, and maintain systems that collect, store, process, and analyze large volumes of data.

What is the role of a data engineer?

The role of a data engineer is to design and implement systems that can efficiently and reliably collect, store, and process large volumes of data. They also need to ensure that the data is accurate, consistent, and available for analysis.

What are some common tools and technologies used in data engineering?

Some common tools and technologies used in data engineering include Hadoop, Spark, Kafka, AWS, Azure, Google Cloud Platform, SQL and NoSQL databases, and data warehousing tools like Snowflake and Redshift.

What are some best practices for data engineering?

Some best practices for data engineering include designing systems for scalability and reliability, using automation tools to manage infrastructure and deployments, adopting a data modeling methodology, and following industry standards for data quality and governance.

What is ETL?

ETL stands for Extract, Transform, Load, which is a process used to move data from one location to another, transform it into a usable format, and load it into a database or data warehouse.

What is a data pipeline?

A data pipeline is a set of tools and processes used to move data from its source to its destination, including extraction, transformation, and loading steps, as well as data validation and quality checks.