Through data engineering methods, we design and build systems to collect, transform and load data to prepare it for further analysis.
Data engineering is based on building data pipelines to extract information from different sources. It converts information into clean data to be used in further processes such as data science, data visualization, and business analytics. Our goal is to provide organized, standard data flow to enable data-driven models.
As data engineers, we develop, construct and maintain architectures to process data in alignment with business requirements. Our methodology involves gathering data requirements, maintaining metadata about data, ensuring security and governance for the data, storing data, and processing data for specific needs. All is done in communication with our clients and in line with their needs, so the result is accurate and specific data ready for future analysis and utilization.
Elimination of bad data
Usage of relevant sources that bring the most value
Stable systems for data collection
A strong basis for further data usage and analysis
An optimal, precise, and solid system for data collection, flow, and storage
We approach data through the main extract, transform, and load process so it can be placed into a targeted repository. Through ETL we combine data from multiple data sources into a single, consistent data store that is loaded into a data warehouse or other target system.
With the data warehousing process, we collect and manage data from varied sources to provide meaningful business insights. We use data warehouse to connect and analyze business data from heterogeneous sources needed for analysis and reporting.
We create subsets of a data warehouse focused on a particular line of business, department, or subject area. With data marts, we make specific data available to a defined group of users. This allows users to quickly access critical and specific insights without wasting time searching through an entire data warehouse. It also improves the security of access since users can view only parts of the data intended for them. Furthermore, data marts secure better reading operations performances since they are optimized for specific users.
Through data lakes, we provide storage for structured or unstructured and raw data, at any scale, from multiple sources in one place. Data lakes store data in its native form before it is needed to run different types of analytics to guide users in making better business decisions. They are useful to data scientists and analysts for ad hoc analysis, and for discovering the possibilities that derive from collected data without the need to consolidate them in the data warehouse first.
We do initial interviews with you to define your goals and expectations. Afterward, we do as is system analysis where we establish if you already have some data engineering processes implemented and in which conditions are they. We check the state of databases, data warehouses, data pipelines, and automation processes.
Through detailed interviews, we set to define project goals and requirements. We create detailed specifications and plan for the implementation phase. The aim is to specify data sources, ETL process design, and business logic that connects data sources. Also, we define data warehouse design, solution architecture, and technology selection.
In this phase, we set up the infrastructure and develop a full-scale solution. Next, we identify and recommend data analytics or data science possibilities once the data engineering part is done.
We do initial interviews with you to define your goals and expectations. Afterward, we do as is system analysis where we establish if you already have some data engineering processes implemented and in which conditions are they. We check the state of databases, data warehouses, data pipelines, and automation processes.
Through detailed interviews, we set to define project goals and requirements. We create detailed specifications and plan for the implementation phase. The aim is to specify data sources, ETL process design, and business logic that connects data sources. Also, we define data warehouse design, solution architecture, and technology selection.
In this phase, we set up the infrastructure and develop a full-scale solution. Next, we identify and recommend data analytics or data science possibilities once the data engineering part is done.
Our first step is understanding and discovering your data sources. From there we pinpoint your problems and define your goals.
We suggest the best way to approach your objectives by deciding on methods and approaches on how to collect and process your data.
You get full support from start to finish with us making sure you fully understand each step.
We aim to prepare your data in the best way possible for further analysis and data science processes.
Our goal is to provide help in designing, operating, and supporting the increasingly complex data environments that power and drive modern data analytics.
Through data engineering, we empower companies to find practical applications of data that drive business success.
By combining and preparing your data from production processes, product management, marketing, or sales, we help you create environments that focus on the most relevant and important data for your business objectives in the fast-moving consumer goods market.
We bring your production process data into a single repository. We drive data from each step in the production, from start to finish, into a data warehouse or lake so you can make decisions that will optimize your production and decrease backlogs.
From your e-commerce data and online buyers’ behavior, we manage the data in one place, so you can acquire relevant insights and metrics on your consumers and clients.
From data collected from your retail stores, we manage information about sales, products, shopping frequency, and stock. Our approach of bringing your data together allows you to get further insights into your consumers and manage products most optimally.
You need a software solution based on data?
Let us help you discover all the clues.