Data Engineering Services To Make Informed Decisions

Data Engineering Services Trusted by the Leading Companies

ThirdEye’s data engineering services transform organizational knowledge into insights for more informed and timely business decisions with the best possible TCO.  

As a data engineering solution partner for enterprises, we take care of the entire data engineering life cycle. We have hands-on expertise in the development, deployment, and maintenance process in building a robust infrastructure to process and manage large volumes of data. ThirdEye team has 100+ years of combined experience in successful big data implementation, database management, modern data architecture development, data integration, and core programming languages such as SQL, Python, R, and Java.  

Data Engineering Services We Offer

Our data engineering services go beyond just “consultation.” We understand what it takes to bring value to your business. We like to create strategic partnerships with our customers by delivering results that create value for money.  

Quick View of Our Data Engineering Offerings:

  • Developing complete end-to-end Data Pipelines  
  • Ingesting Data from various sources into desired destinations  
  • Managing multiple file format conversions  
  • Performing Data Transformations  
  • Performing Data Cleansing  
  • Maintaining Data Integrity  
  • Developing Data Models  
  • Performing ETL and ELT jobs  
  • Enriching Data for downstream Analytical Purposes  
  • Performing Data Analytics  
  • Performance Tuning  
  • Big Data Implementation Across Enterprise 

Our Expertise in the Data Engineering Field:

ThirdEye’s data warehousing solutions provide a centralized repository for storing and managing large volumes of data. Our solutions leverage all tools for data modeling, querying, and analysis, enabling organizations to make informed decisions based on their data

We work with all kinds of modern data architectures for storing and processing large volumes of data and setting up data platforms. Data platforms enable organizations to collect, manage, and analyze data from various sources, providing insights into their operations, customers, and markets.

With data governance, we set up policies, procedures, and standards for managing data, ensuring compliance with regulations, and protecting data privacy and security. Scaling up the process of managing the availability, usability, integrity, and security of the data used in an organization. 

As we know, data analytics is an approach to analyze the collected and processed data to get deep insights. The insights gained from data analysis are then used to make informed decisions, such as improving products, optimizing operations, and identifying new market opportunities. 

We work closely with our customers to implement Big Data infrastructures that leverage and extend their current or build new IT infrastructure with the lowest possible TCO. We specialize in software tools, such as Hadoop, Spark, and NoSQL databases, which are designed to handle massive amounts of data across distributed computing environments. 

Data quality check solutions help enterprises to ensure the accuracy, completeness, and consistency of their data. These solutions leverage tools for data profiling, data cleansing, and data enrichment. Data quality checks are critical to ensure the effectiveness and reliability of data-driven decision-making.

ETL stands for Extract, Transform, and Load. Through ETL jobs, we automate the process of extracting data from various sources, transforming it into a familiar format, and loading it into a target system. These solutions help enterprises to streamline their data integration processes and ensure data quality and integrity.

The process of transforming raw data into interactive and visually appealing representations, such as charts, graphs, and dashboards is called data visualization. It helps enterprises monitor performance, communicate information, and discover patterns and insights. Users can make informed decisions based on the insights gained from the data visualization output. 

The Crucial Phases of Our Data Engineering Process

Data Pipelines

Data Pipelines

Building a data pipeline is not an easy feat, but the payoff of owning your own data and being able to analyze it for business outcomes is huge.
ThirdEye has considerable experience in developing data pipelines, either from scratch or using the services provided by major cloud platform vendors – Azure, AWS, and Google.

Data Lake

Data Lakes

Building a Data Lake is easy as it is simply about centralization of data, irrespective of its sources in its raw formats. However, having the knowledge and experience to extract meaningful insights from all that data is not an easy task.
ThirdEye can set up your data lake and get you going on your Big Data journey.

Data Analytics

Data Analytics initiatives help businesses increase revenues, improve operational efficiency, optimize marketing campaigns & customer service efforts, respond more quickly to emerging market trends, and gain a competitive edge over rivals.
ThirdEye can help you build a real-time data analytics platform.

Our Expertise in the Advanced Data Engineering Tools & Technologies

At ThirdEye, our data engineers focus on bringing maximum value to your investments. Therefore, we give special attention to selecting impactful and cost-effective tools & technologies to deliver tangible results for your business. 

Function of this phase: It is necessary to identify, extract, and load data from various sources. This phase is mandatory for enterprises that do not have a clear idea of their data potential.  

Tools and technologies we use in this phase:  

  • Data discovery tools: Alteryx Designer, Trifacta Wrangler  
  • Data extraction tools: Apache Sqoop, Apache Flume, Apache Kafka  
  • Data transfer tools: AWS Glue, Azure Data Factory, Google Cloud Dataflow  

Function of this phase: Enterprises usually deal with unstructured, semi-structured, and structured data patterns. In this phase, we clean, format, and organize data for analysis.  

Tools and technologies we use in this phase:  

  • Programming languages: Python (with libraries like Pandas, and Spark), Scala (with Spark)  
  • Data transformation frameworks: Apache Spark, Apache Beam, Flink  
  • ETL/ELT tools: Informatica PowerCenter, Talend Open Studio, Microsoft SSIS  

Function of this phase: We store and manage data in a secure and accessible way for the decision-makers.  

Tools and technologies we use in this phase:  

  • Data warehousing: Amazon Redshift, Microsoft SQL Server Analysis Services, Snowflake  
  • Data lakes: Amazon S3, Azure Data Lake Storage, Google Cloud Storage  
  • Data catalogs: Collibra, Alteryx Data Catalog, Azure Purview  

Function of this phase: We automate the flow of data between stages for faster and real-time results.  

Tools and technologies we use in this phase:   

  • Workflow orchestration tools: Apache Airflow, Luigi, Prefect  
  • Cloud-based orchestration services: AWS Step Functions, Azure Data Factory, Google Cloud Workflows   

Function of this phase: This is one of the vital phases to ensure data accuracy, completeness, and consistency.   

Tools and technologies we use in this phase:  

  • Data quality frameworks: Open Data Quality, Trifacta Data Wrangler  
  • Data monitoring tools: Datadog, Splunk, Dynatrace

Function of this phase: With this phase of actions, we protect data assets and ensure compliance with regulations like GDPR and HIPAA.  

Tools and technologies we use in this phase:  

  • Data encryption tools: AWS KMS, Azure Key Vault, Google Cloud Key Management Service  
  • Data governance platforms: Informatica Enterprise Data Catalog, Collibra, Azure Purview

Function of this phase: This is the final phase of data engineering. Once the data is prepared and accessible, data visualization is used for in-depth analysis and further communications like recommendations, reporting, and notifications.  

Tools and technologies we use in this phase:  

  • Dashboard & Reporting: Tableau, Power BI, QlikView, Looker  
  • Open-Source Data Visualization: Matplotlib, Seaborn, ggplot2   

Customer Success Stories

Healthcare Analytics Platform for Private Practicing Professionals

Developed and launched a comprehensive healthcare analytics platform designed to empower private practicing healthcare professionals with data-driven insights.

Optimizing Lead Conversion with ML - NAVIK Converter

Developed and Launched NAVIK Converter - helping enterprises achieve the maximum benefits from their Big Data and optimize lead conversions.

Order Management System for Enhancing Efficiency and Customer Engagement

Developed a next-generation order management system for a leading oilfield equipment and services provider. The objective was to enhance operational efficiency, improve customer engagement.

Is your organization planning to manage and analyze data more effectively?

ThirdEye can provide you with expert data engineering consultation and services that will help you unlock the full value of your data.  

Our team of data engineers will work closely with you to design, build, and implement scalable data pipelines that integrate seamlessly with your existing infrastructure. From data warehousing to real-time data processing, we have the expertise and experience to ensure that your enterprise's data is accessible, accurate, and actionable.  

Contact us today to learn more about our big data consultation and data engineering services and how we can help you turn your data into a competitive advantage.