Empower your organisation with data using modern Data Engineering stack
According to experts and our own experience close to 80% of work in data projects is data collection and cleaning. Data engineering can often be time-demanding and challenging. We will help you with crucial steps in your big data project.
At 10 Senses, we always think about the final applications and analyses, where the data will be used, and use a modern data engineering tech stack. See the technologies we use.
Building data pipelines
To activate your data it usually needs to be moved from the place of its storage. We will carry out all the steps needed to prepare your data for ingestion in business tools.
ETL / ELT
In order to prepare your data for analysis it is necessary to execute data transformation tasks. We will do the work around Extract-Transform-Load and Extract-Load-Transform.
Integrating third party APIs
Data from third parties are powerful. However, they often are accessible only through dedicated APIs and require custom data transformations. But we will take care of that.
Processing semi-structured data
Not all data in stored in your IT systems is relational with fixed schemas. In such case, we know how effectively handle such data.
Master data management
Single source of truth has many benefits for your organisation. For this reason we put emphasis on issues such as avoiding data redundancy, incosistencies or handling change requests.
Data governance
Data quality is the cornerstone of organisation-wide data accessibility. That is why we put special care about data governance when working with data.
Do you have any questions regarding Data Engineering in mind?
Let’s check if we can help you
We do Data Engineering with an analytics end goal in mind
But why should you care?
With engineering developed the right way you minimise the number of potential errors and get data which you can trust. It will pay dividend when you feed the data into business intelligence or machine learning.
At 10 Senses we always do data engineering with business intelligence and machine learning as the end goal. We know that with a proper data engineering setup it is way easier to implement new analytics solutions. So you save time and money.
We work in two ways and the choice really depends on your needs and the approach of your company towards data-related projects. We either run the whole project or provide staff augmentation.
Project: We take care of managing the project from the first draft up to final delivery. You do not need to recruit people, assign them tasks or make decisions on technology.
Staff augmentation: You manage the project and the people we provide you with function as part of your team. We take care of recruitment and providing you with talent.
Regardless of the mode of cooperation we guarantee people with top-notch skills who can handle even the most demanding data tasks.