Today’s companies generate a tremendous amount of data, which must be optimized and turned into useful information. Data engineering has been a critical field when it comes to data, but few people understand what it entails. Data engineering is to gain new insights from data for business transformation. Businesses of all sizes rely on data to run their operations. Businesses use data to answer relevant inquiries regarding consumer interest and product viability. Access to data is essential to scaling a business and gaining valuable insights.

Data engineering performs sourcing, transformation, and managing data from various sources. A valuable and accessible data set is created through this process. A major focus of data engineering is analyzing and collecting data. Artificial intelligence and data integration tools gather, authenticate, and integrate data in data engineering.

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    8 Y-Combinator Backed with Companies

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    400+ Projects Completed

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    $400m+ Funds Raised By Clients

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    10+ Yrs of Building Digital Products

Take your Business to Next Level with Customized and Powerful Data Insights

We empower users with agile and intuitive processes by providing them with analytics and engineering services from WAL. Our team helps organizations leverage data and analytics to create new revenue streams and business models, ensuring data quality, security, and regulatory compliance. By combining artificial intelligence and process automation, our solutions assist you in making better decisions. In addition, WAL’s data-powered consulting delivers tangible results by securing innovation and scaling programs. Our data pipelines create robust data and reduce the processing time of queries. By providing ETL and data warehouse services, our experts generate faster insights.

Integrated End-to-End Data Engineering Services

Data ​Ingestion​

Data ​Ingestion​

We retrieve unstructured and structured data from streaming and batch sources. Our team refines/cleanses data before releasing it to legacy database systems or cloud systems and business users for analysis and exploration.

Data Storage

Data Storage

A data analysis technique for extracting, processing, transforming, loading, and storing data in relational, non-relational, NoSQL, big data, or cloud storage, based on data availability and type.

Modernization of Data

Modernization of Data

We migrate data onto or from on-premises legacy systems and onto new platforms or cloud storage infrastructure.

Data Pipelines

Data Pipelines

We develop repeatable and independent data pipelines utilizing different legacy, Big Data, and cloud data management technologies. WAL implements techniques such as DataFrame, Synapse, DataBricks, and Informatica for batch and real-time data processing.

Data CI/CD

Data CI/CD

Expertise in legacy and cloud deployment services for building efficient production processes using infrastructure-as-code artifacts, application data, database objects, data pipelines, and data validation.

Routing Insights and Real-Time Analysis

Routing Insights and Real-Time Analysis

Data processing systems with real-time and batch capabilities incorporate mobile, web hosting, and cloud technologies.

A curated approach to monetize and maximize the value of data

WAL offers complete data engineering services to our clients. We are committed to assisting them in understanding their data-related challenges. 

Enterprise Application
  • Efficient time to value

    By leveraging accelerators, frameworks, and proven centralized services without compromising quality

  • Indepth research on customer and markets

    Gain new insights into consumer behavior and inventory levels by integrating retail data and market research

  • Higher sales

    By using online/e-commerce data for sales initiatives

  • Improved compliance

    Integrate market and regulatory information to align sales and distribution

  • Maximizing operational efficiency

    WAL makes operations more efficient and effective. We implement machine learning and artificial intelligence to improve sales and operations. Our team uses distributor data to identify gaps, improve replenishment rates, and enhance supply chain visibility.

Tools & Technologies

With a large number of visitors increasingly accessing websites from mobile devices and tablets, it is imperative that your website, business and consumer web applications render well across all these form factors besides the desktop. We are skilled in cutting-edge technologies for creative technical execution.

Server Side Technologies

  • Ruby

    Ruby

  • Wordpress

    Wordpress

  • Python

    Python

  • PHP

    PHP

  • Java

    Java

  • Microsoft .Net

    Microsoft .Net

  • Node Js

    Node Js

Infrastructure Services

  • AWS

    AWS

  • Circle ci

    Circle ci

  • Google Cloud

    Google Cloud

  • Github

    Github

  • Jenkins

    Jenkins

  • Heroku

    Heroku

  • Kubernets

    Kubernets

  • Ansible

    Ansible

  • Digital Ocean

    Digital Ocean

  • Terraform

    Terraform

  • Azure

    Azure

Frontend technologies

  • React Native

    React Native

  • Angular

    Angular

  • Vue.Js

    Vue.Js

  • Electron

    Electron

Databases

  • My Sql

    My Sql

  • Redis

    Redis

  • SQL Server

    SQL Server

  • Postgre Sql

    Postgre Sql

  • Elatic Search

    Elatic Search

  • Mongo DB

    Mongo DB

Frequently Asked Questions

What are Data Engineering Services ?

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Data engineering facilitates the use and accessibility of data for consumers. Consequently, data engineers must gather data from several sources, transform it, and analyze the results.

What is the Difference Between a Data Engineer and Data Scientist?

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Data Scientists and Data Engineers differ in their areas of focus. Data Engineers are responsible for building data infrastructure and architecture. Data Scientists perform advanced mathematics and statistical analyses of data collected. Data engineers also create complex query languages to make the data more accessible. Business analysts tend to focus more on identifying solutions for critical business problems, such as improving customer service, reducing costs, and optimizing operations.

What are the Benefits of Data Engineering ?

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A list of the top 4 benefits of data engineering

  • By using data-driven insights, companies can improve their decision-making, leading to better results. 
  • Assessing the Impact of Decisions.
  • Enhancing the User Experience by Predicting the User Story.
  • The identification of new business opportunities.

We help turn your ideas into flawless digital products by developing custom software solutions websites and mobile applications that convey your brand’s story.

Startups Collaborated

8 Y-Combinator

startups collaborated
Startups Collaborated

350+

products built

Trusted By Leading Brands And Startups

NateraThe Ritz-CarltonEmcore
SamsungJohnson & JohnsonTrimble

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