Abstract: According to the report, slightly more than half of our data scientists (51%) are spending most of their time working with unstructured datasets. They are forced to spend their significant time on the data engineers work, but they should not. In this talk, we will describe how companies can benefit from outsourcing data engineering. We will also introduce the possible use cases with our services: Data Cleaning, Labeling, Organizing, ETL, Data Warehouses, Data Architecture and Data Analytics, Data Pipelines, Data Collection and Mining, DataOps and MLOps. At the end, we will briefly speak about Ralabs and our existing data engineering case study - ConDati (https://ralabs.org/cases/marketing-analytics-tool/).
Bio: Working as engineer Roman found that his peers, Data Scientists are spending a lot of their time on work that was not at all interesting for them and at the same time, due to lack of excitement in data engineering, a big issue was found with performance and quality.
He decided to help his friends and implemented a process that allowed them to move some tasks from Science to Engineering department, thus increasing the overall performance, quality and its colleagues’ happiness. Later he and his friend Roman found a company that specializes in these types of services, nowadays known as Ralabs. Today Ralabs is making Data Scientists happy from companies like Forbes, Capitalise, CR2, and others.
PS: Roman in the industry for more than 10 years. At some point, he was an engineer, team lead, architect, manager, etc.. Also, Roman ran Google Group in Ukraine.