Data Engineering Services
Cleanse, model, and turn your data sets into robust ecosystems with our data engineering services.
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Are you interested to learn more about our Data Engineering services?
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- We sign NDA
What happens after you contact us?
Our solution experts will answer your questions in a secure online meeting. You will get good information and honest advice in plain English. You are then free to choose how to move forward.
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Data Engineering Services
Data Cleansing
A wrong dataset can lead to disastrous decisions. That’s why we offer data cleansing services that involve removing typos, errors, and duplicate entries from datasets. We do this with automated tools. No matter how decayed your file is, we can clean it up with advanced solutions to improve data quality multifold.
ETL & ELT Jobs
Data extraction is more manageable with our updated ETL/ELT services. Whichever is your data source, we can access and move it to desired repositories like data lakes or data warehouses to help you draw meaningful insights. So, you needn’t get worked up with data extraction, transformation, or loading.
Data Ingestion
With upgraded data ingestion methods, we adapt incoming data into required structures. Our highly-able data engineers can lend you a hand for all your data ingestion needs - regardless of whether you need data to be ingested in real-time or in batches. And that’s what makes us your go-to partner.
Data Visualization
Developing graphically-rich analytical platforms is our forte. Our talented data engineers first dig into your needs. We then create interactive UIs that reflect your complex datasets in the form of colorful pie charts, bar graphs, heatmaps, etc., to help you understand the true stories your data always wanted to tell.
Real-time Data Processing
We have specialized skills in processing bulk data in real-time. Our real-time data processing solutions ensure short latencies, so there are no long pauses before getting the processed output. Many of our esteemed clients have benefited from our real-time solutions that have helped them gather instant reports for quicker decisions.
Data Migration
Is it becoming too much to maintain data in your legacy store? Let us move your files from the old store to a new one. With custom rules, we move bulk data automatically. We migrate data manually, too, if required. Our T-shaped experts are here to address every challenge while preserving your historical data.
Data Pipeline
Creating an effective data pipeline is crucial for shorter delivery cycles and fast turnarounds. Therefore, we use robust methods to enable quick data flow between systems, apps, and platforms. Our chain of processes ensures the swift movement of data required for today’s fast-paced needs.
Data Modeling
We employ certified data engineers who can help you view data structures better. Our experts can show you interdependencies or relations between two or more data clusters and points. By enabling you to connect these dots, we help you get insights that you may not have known existed.
Cloud Data Solutions
Hire us to experience a pain-free data migration from your on-premise servers to the cloud. Because we have hands-on experience in Azure, AWS, and Google cloud engineering, you can rely on us to perform some of the most demanding database hosting tasks that add business agility while keeping your costs low.
Data Modernization
Increase business agility and leverage valuable insights for best business outcomes by moving and modernizing dataflows from on-premises legacy systems to the cloud. At Capital Numbers, we offer end-to-end data modernization services, including database management services and managed advanced data analytics & BI. Thereby helping you create future-ready, high-speed, scalable data solutions.
Let's Discuss Your Project
We're happy to hear your project goals and turn them into a next-level digital product. Get a free consultation to make this happen!
How Does Our Data Engineering Process Work?
Requirement Analysis
Identifying Data Sources
Creating a Data Lake
Implementing Data Pipelines
Testing Data Quality
Deployment
Requirement Analysis
Firstly, our data engineers and business analysts conduct discovery calls with potential clients. During this stage, we try to go deep into the functional and technical requirements of the project.
Identifying Data Sources
Once we know the requirements, we review the current data sources. We also identify sources from which we need to gather future data.
Creating a Data Lake
After assessing the data sources, we create a data lake which we populate with raw data. We keep all unprocessed data in this data lake.
Implementing Data Pipelines
Once we centralize all raw files, we begin the data processing job. We start sourcing, formatting, resizing, unifying, and transforming data from raw files.
Testing Data Quality
After processing the data, we conduct thorough testing (either automated or manual, depending on the needs). We check the data flow and quality at this stage before finally deploying on the live server.
Deployment
In this crucial step, we bring our DevOps team to deploy the processed data into the chosen environment smoothly. An efficient deployment from our team ensures better analysis and availability of data down the road.
The tools we use to address your data challenges
To offer our clients complete scalability, simplified maintenance, and effective cost management, we offer solutions based on cloud services. The platforms we use are Amazon Web Services, Microsoft Azure, and Google Cloud Platform.
To help our clients take full advantage of the power of big data, we build data lakes and data pipelines. We also use distributed processing solutions together with orchestration tools such as Spark, Hadoop, Hive, Presto, Kafka, and Airflow.
We help our clients optimize their transactional databases and build advanced analytical systems by implementing ETL processes, data pipelines, data warehouses, and data marts using MySql, PostgreSQL, Oracle, Redshift, and BigQuery.
Dedicated solutions such as NoSQL databases improve working with unstructured data, which many of our clients have. To streamline the process, we use tools such as MongoDB, DynamoDB, Cassandra, and HBase.
By implementing business intelligence solutions we help our clients become fully data-driven companies and stay ahead of their competition. We specialize in Tableau and PowerBI.
Using leading market tools, for example Elasticsearch, Logstash, and Kibana, we implement solutions such as full-text search, log-parsing engines, and analytics platforms.
We use tools such as Kinesis, DataFlow, Storm, and Flink to help our clients process and analyze large amounts of data in real time.
Industries We Serve
Our data engineers have helped businesses across industries leverage data in a way that drives results, not costs. Some such industries that we’ve served are:
- Geospatial
- Energy
- eCommerce
- Gaming
- Retail
- FinTech
Let's Discuss Your Project
We're happy to hear your project goals and turn them into a next-level digital product. Get a free consultation to make this happen!