Your corporate data can be one of the most efficient instruments in your toolset. How to make it possible? CHI Software delivers robust data engineering solutions that match your needs and goals. Partner with us to enhance your data management, optimize performance, and drive informed decision-making for sustainable growth.
We build a strong foundation for all your data management initiatives. Our job here is to develop comprehensive data models, databases, and data warehouses tailored to your business needs. This is a corset for growth and efficiency, defining your workflow.
Our data engineers design and manage ETL processes to extract data from various sources, transform it into meaningful formats, and load it into your data systems. These services help you ensure your data is clean and ready for analysis.
Achieve a holistic view of your data with our data integration services. Our data engineering experts collect data sets from multiple sources under one roof to give you a bigger picture of all your operations. In other words, we draw a map of your business opportunities to help you pave the way for change.
Where do you store structured and unstructured information? Let our data engineering company answer this question for you. We build scalable data warehouses supporting data retrieval and powerful analytics. Anytime you need a specific data set – here it is, offering all the required information.
Harness the potential of large data sets with our data engineering consulting services. We develop platforms with tools like Hadoop, Spark, and NoSQL databases to handle vast amounts of data and help you always be on the alert. Our solutions enable real-time data analytics and predictive modeling, driving business innovation.
Welcome to the cloud, where we build cost-effective and scalable data platforms for you. CHI Software uses the powers of AWS, Azure, and Google Cloud to provide quality and security at each step of your data management operations. Clear any hurdles on the way to data-driven business decisions.
Do you want your data to flow seamlessly without human involvement? CHI Software engineers make it real. Well-designed data pipeline automation opens the door to reduced errors and continuous data processing. Trust monotonous tasks to technologies while you’re busy with more important things.
Our meticulous planning and execution guarantee a smooth data migration, whether you’re upgrading data systems or moving to the cloud. If you aim for maximum accuracy and high availability, you’ve got to the right place. Conduct successful transformations with professional assistance and support.
Efficient Data Management How is it even possible to manage every data piece? Data engineers know the answer! They can clean, validate, and organize your corporate information to ensure you always receive reliable insights and analytics.
Enhanced Decision-Making That’s the cornerstone of data engineering as a service. Who runs the world? Businesses that process their data! Forget about assumptions or suggestions – now you can get real-time analysis at any moment.
Cost Reduction Data engineering services automate several manual operations at once, reducing the chances of errors. Naturally, such robust systems will save you not only money but a good portion of your working time.
Competitive Edge The faster you take hold of your data, the faster you may appear among business leaders. Turning to data engineering service providers is your sure way to better strategies, streamlined data operations, and, most importantly, improved customer experiences.
Powerful Scalability Your data grows with your business. So, how can you deal with it properly without compromising performance? Don’t think much – just contact experts from our data engineering firm. Grow your business steadily and prepare yourself for success.
Access to Advanced Data Analytics and AI Sooner rather than later, you’ll start using advanced AI tools. A well-designed data infrastructure is your entry ticket to providing all kinds of AI and machine learning solutions. Algorithms need data quality, and you’ll be ready to provide it at a moment’s notice.
• Python Libraries: pandas, Prefect, Kafka-Python, Apache • Airflow, PySpark, SQLAlchemy, Polars, Dask, dbt, and more
• Scala, Java
• SQL, T-SQL, HSQLDB, PL/SQL
• Big Data Distributions: Cloudera, Hortonworks, MapR, Databricks, AWS EMR
• Big Data Tools: HDFS, Apache Hive, Apache Pig, Apache Flink
• NoSQL Databases: Cassandra MongoDB, Hbase, Phoenix
• Process Automation: Oozie, Apache Airflow
• Analytical Databases: Big Query, Redshift, Synapse
• ETL: Databricks, DataFlow, DataPrep
• Scalable Compute Engines: GKE, AKS, EC2, DataProc
• Process Orchestration: AirFlow, Bat
• Platform Deployment & Scaling: Terraform
• Power BI
• Tableau
• Data Studio
• D3.js
By partnering with us, you hire the best cloud engineering talents. We work with the most trusted and popular cloud platforms, such as AWS, Microsoft Azure, and Google Cloud, to exceed your expectations in quality and agility.
Just think of the business innovation, and we’ll be there to turn your thoughts into reality. Our team specializes in generative AI, chatbot development, computer vision, and face recognition to help you grow and succeed.
Thanks to our profound expertise, we know how the software development industry works and how your business can become a part of it. You can trust us with the most challenging projects, and we’ll solve them, just like we always do.
Where do you store your data? At the initial stage, our task is to collect raw data from diverse sources (databases, files, APIs, etc.) relevant to our data engineering project.
Now, we must get ready for the central part of our work and clean out the data we’ve collected. Our data engineers remove or correct errors, duplicates, and inconsistencies. It’s also important to handle missing values.
Our team sets up a dedicated storage for all the cleaned and properly formatted data in a database, data warehouse, or data lake.
As a data engineering company, we always make sure all the prepared data meets validation rules and passes quality checks. Otherwise, we’ll probably have to cope with data issues quite soon.
Now, the dataset is ready to move forward, and our data engineering experts load it into the analytics or business intelligence platform of your choice.
But our work doesn’t end with data loading. We also document the data lineage, schema, and other metadata to facilitate data governance and discovery.
This is the final but vital step ensuring the project’s success in the long run. We continuously monitor data quality for smooth operation and solve emerging issues as soon as possible.
Our client is a US-based clean energy company. Their solution combines financial and technological innovation to accelerate the deployment of solar, wind, and other critical infrastructure worldwide.
Our client is an Azure expert enterprise, and SaaS management platform holder specializing in client support, consulting and coast management, encountering individualized requests from various clients requesting reports.
In this project, we're creating three super important solutions for a language tech company. First, an intelligent question-answering system to automate responses. Second, a smart scraper with advanced DOM analysis
Here are the key points you need to understand to build a strong foundation for your data management efforts.
Data engineering involves building data collection and processing systems, ensuring data quality and accessibility at any given moment. Simply put, data engineering firms keep all of your data in order so that you can use it in business planning.
Data science goes further by analyzing data to provide valuable insights that you could miss in your analysis. So, it all starts with data engineers creating a proper infrastructure, and then data scientists turn data into insights. As you can see, these two spheres are complementary.
There is more than one way you can benefit from data engineering:
- First, you can make informed decisions by using all relevant data and correctly processing it;
- Data engineering automates data workflows, which means less manual work and more efficiency across departments;
- You can respond to all market trends and shifts faster thanks to real-time data processing;
- Finally, data engineering services are a foundation for your AI innovations, as they help prepare the infrastructure needed for algorithm training.
Importantly, not only big tech companies can utilize data engineering and data science innovations. Startups and mid-sized businesses can join too! If you need guidance on where to start, just leave us a quick note.
CHI Software follows these steps during data engineering projects:
1. Analyzing requirements and conducting market research to understand the client’s goals and process bottlenecks;
2. Collecting data from various sources in one place;
3. Designing scalable data storages like data lakes or warehouses;
4. Building data pipelines to clean and transform available data sets;
5.Managing data to provide better quality and security;
6. Implementing the approved solution and continuously monitoring it if needed.
Data engineering tools are equally good at processing structured, semi-structured, and unstructured information. By structured data, we understand databases and spreadsheets. Unstructured data includes social media content and comments, logs, and documents. Semi-structured data is JSON and XML files.
Moreover, data engineering solutions can cope with real-time data streams from IoT devices, sensors, and APIs, as well as big data from systems like Hadoop and Spark.
Protecting data is always a multi-faceted process that includes several steps and areas of protection. Our best practices include:
1. Multiple protection methods at once, such as data encryption at rest and in transit, access controls, and security audits;
2. Data governance and compliance with standards like GDPR and HIPAA;
3. Secure coding practices during our development process;
4. Monitoring and logging to promptly respond to security threats.
All the main steps of data engineering may be a challenge at some point. That’s why you need an expert team for troubleshooting. The main challenges include:
- Handling large volumes of data without sacrificing quality and consistency;
- Scalability issues as data starts growing;
- Managing real-time data flows;
- Ensuring data security and compliance;
- Adapting to emerging trends and technologies.
Sure! For example, we built a real-time analytics platform for a retail company that integrated data from multiple sources, providing actionable insights that increased sales by 15%.
Another project involved developing a scalable data warehouse for a financial services firm, which improved their data processing speed by 40%.
We also implemented a data lake solution for a healthcare provider, enabling advanced analytics and improving patient care outcomes.
If you want to learn more, visit our Case Studies page.
As often happens, the project’s time frame varies depending on the scope and complexity. We need to know more about you, your industry, and the critical features you want to implement first. But you don’t have to drift in darkness – we’ll provide you with a rough project estimation after the first call.
Note that a small to medium-sized data engineering project can take from a few weeks to a few months. Larger, more complex data analytics applications with custom development may take several months to a year.
After your solution is deployed, we can ensure smooth day-to-day operation and continuous optimization of your solution. Our engineers monitor your software and address issues as soon as they emerge. We also help you adapt to changes with regular updates and improvements and provide training and documentation upon request.
About cookies on this site