Data Engineering Services
We offer comprehensive support to our customers with data engineering services. From unprocessed data to usable information using Data Lakes, Delta Tables, Streaming applications, Data Warehouses, and DataOps.
Data Engineering Consulting Service
How We Support Clients in Data Engineering?
Our Data Engineering practice is focused on designing and building reliable systems for data ingestion, gathering, storage, and analytics. This practice is important in nearly every industry; it supports countless aspects of data science.
Our Data Engineers facilitate seamless access to data by performing complex analyses on raw data and developing sophisticated Data Pipelines and Data Platforms. Without advanced data engineering, it would be extremely difficult to make sense of the enormous amounts of data organizations have available. By leveraging cutting-edge technologies and methodologies, we ensure that data is not only Accessible but also Actionable, empowering companies to make informed decisions and maintain a competitive edge in their respective markets.
Who are our Data Engineering consultants?
Data engineers are experts in several programming languages that are used to develop a data platform. They ensure the creation of data pipelines that allow data to be moved easily from one system to another. They also transform data from one format to another, making it easier for data scientists to access and analyze data from different sources.
By building and maintaining these pipelines, data engineers ensure that data is:
1. consistently available,
2. properly formatted,
3. and ready for complex analytical processes.
Their activities are essential to the consolidation of separate systems that process data, hence aiding in proper data analysis and promoting data-informed decision-making in organizations.
What are Data Engineering Services?
Innoworks Data Engineering services are implemented to take your business to a new level for data usage, management, and automation. Through our automated data pipelines, you are able to extract valuable insights without much hassle of manual data handling.
• Our expert team supports global enterprises such as Porsche, RR and SITA in developing sophisticated data processing pipelines.
• We collaborate with our clients for the derivation of critical business information, optimization of data management, and top standards of data quality and availability.
Our strategic project approach and comprehensive data engineering services empower companies to make informed decisions.
Look at our data-related service suite (case studies) and discover how Innoworks solutions will revolutionize your business.
Audit and future-proof, scalable dataflows
Confident of their process being in a soundly robust position, the company retained the Innoworks Team to conduct an end-to-end audit and ensure it is truly bullet-proof.
Data Engineering development lifecycle
Understanding Business Requirements and Technical Requirements
We are one of the oldest data engineering companies worldwide. We work with clients worldwide to maximize data value extracted day in and out.
Firstly, our data engineering team leads the workshops and discovery calls with potential end-users. Then we draw all the necessary information from the technical departments.
Let’s have a discussion on a data engineering solution for your business!
Analysis of existing and future data sources
At this juncture, it is now important to check the current sources of data with the aim of maximizing the utility of data. You should list several sources for structured and unstructured data you can collect data from.
While at this stage, our team will prioritize them and evaluate those.
Building and Implementing the Data Lake
Data Lakes are the cheapest option to store data. A data lake is a system for a repository of data which stores raw and processed, structured and unstructured data files. A system like stores flat, source, transformed, or raw files.
Data Lakes can be established or accessed with certain tools, for example, Hadoop, S3, GCS, or Azure Data Lake on-premises or in the cloud.
Designing and implementing Data Pipelines
After selecting data sources and storage, the next step is the development of data processing jobs.
These are the most critical activities in a data pipeline as they change data into relevant information and generate unified data models.
Automation and deployment
The next part is one of the most important parts in data development consulting – DevOps. Our team develops the right DevOps strategy for deploying and automating the data pipeline.
This strategy plays an important role as it helps to save a lot of time spent, as well as take care of the management and deployment of the pipeline.
Testing
Testing, measuring, and learning — are important at the last stage of the Data Engineering Consulting Process.
DevOps automation is vital at this moment.
Industry expertise
Healthcare
We provides data engineering solutions for healthcare, enabling secure, scalable, and compliant data pipelines for improved patient care, predictive analytics, and operational efficiency. Our expertise ensures seamless data integration, real-time processing, and AI-driven insights to enhance clinical decision-making and healthcare innovation.
Retail
We provides data engineering solutions for retail, enabling businesses to optimize customer insights, inventory management, and sales forecasting through scalable data pipelines and advanced analytics. Our solutions ensure real-time data processing, personalization, and compliance, enhancing operational efficiency and customer experiences.
Manufacturing
We give data engineering solutions for manufacturing. This allows for the integration of data, analytics with real-time capabilities, and predictive maintenance for efficiency in production, among others. Our solutions are based on AI-driven insights, IoT connectivity, and scalable cloud architectures to enhance decision-making and drive digital transformation in the manufacturing industry.
Data Engineering Tools and Technologies
The Innoworks team uses the best-in-class tools and technologies available in the market. To develop reliable and high-quality software, we partner with best-in-class cloud solution providers, such as AWS, Azure, and GCP.
Our data engineering team employs a full suite of tools to ensure robust data management:
• Data Platforms: We work with Databricks, Cloudera, and Snowflake and other data platforms that support large-scale data processing and storage solutions.
• Data Observability: Tools like Datadog, Grafana, and Prometheus monitor and provide us with insights regarding data pipelines running smoothly and effectively.
• DataOps: We employ DataOps tools like Apache NiFi, Airflow, and dbt, which is also known as data build tool. These tools assist in automating, orchestrating, and managing data workflows and pipelines.
• Data Quality Testing: To ensure good data quality, we use the testing tools provided by Great Expectations, Deequ, and Talend for the detection and rectification of data issues at an early stage.
• Data Transformation: Apache Beam, Talend, and Informatica tools are used to transform data. The data would be formatted well and ready to be analyzed with the help of these tools.
In addition, we are highly dedicated to the open-source community and technologies, making sure our customers take advantage of some of the most popular and efficient data engineering software without the added cost. This way, we can present solid, low-cost solutions answering diverse needs among our customers.
Technology stack
Microsoft Fabric – It is an end-to-end data analytics and AI platform that integrates data engineering, data science, real-time analytics, and business intelligence (BI) into a unified SaaS solution, enabling seamless data governance, security, and compliance across enterprise workflows.
Databricks – Databricks is a cloud-based platform for big data processing and analysis based on Apache Spark. It provides a collaborative work environment for data scientists, engineers, and business analysts. It features an interactive workspace, distributed computing, machine learning, and integration with popular big data tools. Databricks is cloud-based, but it also offers a free community edition that allows users to have an environment for learning and prototyping with Apache Spark. The Community Edition features a workspace containing limited compute resources, a subset of features of the full Databricks platform, and access to a subset of community content and resources.
Cloudera-It provides a hybrid data platform that ensures secure data management and allows portable cloud native data analytics.
Snowflake – The Snowflake Data Cloud is an elastic cloud platform for data in real-time. It allows organizations to share securely and analyze real-time data in the cloud.
Data Build Tool – dbt is an open-source command-line tool for analytics and data engineering that enhances transformation of data within a data warehouse.
Airbyte: Airbyte is an open-source data integration engine that simplifies the unification of data across different warehouses, lakes, and databases. Wherever you are, we can offer a complete, end-to-end data engineering solution
Modern Data Pipelines
Designing, building, and deploying production-quality, end-to-end automated data pipelines.
The Innoworks data engineering consulting team has a strong experience in the implementation of automated data pipelines, both on-premises and in the cloud.
Data Preparation and ETL/ELT
Data preparation, processing, and ETL/ELT (extract, transform (load), load (transform)) help in the processing, transformation, and loading of data into the required data model for business reporting and advanced analytics. Our Data Engineering team has developed such pipelines for many business departments like Finance, Sales, Supply Chain, and so on.
Data Lake Implementation
Data Lakes are the most powerful and creative option for cost-effective data storage and fast processing. In your company, adoption of Data Lakes may help you in business data architecture extension. Innoworks has employed Data Lake solutions to solve numerous client business challenges such as Product Traceability, Customer Data Platforms, IoT data reporting, etc.
Cloud Data Architecture
Today, it is crucial to build and design flexible and highly accessible business data architectures. Our Data Architects can help your business get to the next level in terms of data analytics foundation by combining experience from several large enterprises. Try our Big Data Engineering Services!