and design custom solutions and pipelines. They may build their data pipelines using SQL or Python scripts or Hadoop workflows. However, this option is time-consuming, labor-intensive, and error-prone despite offering great compatibility and usability. ...
The techniques underlying this goal are usually known as Extraction, Transformation and Loading (ETL) pipelines, which aim to organise dispersed data into a common structure. However, despite their popularity and widespread use, these pipelines present a few drawbacks in specific scenarios. In ...
Expertise in data manipulation and analysis using SQL and BigQuery. Experience with Google Cloud Platform (GCP) and Vertex AI. Knowledge of statistical modeling and machine learning algorithms. Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Experience leveragin...
Dataddo is a no-coding, cloud-based ETL platform that provides technical and non-technical users with fully flexible data integration – with a wide range of connectors and fully customizable metrics, Dataddo simplifies the process of creating data pipelines. Dataddo fits into the data architecture...
Knowledge of statistical modeling and machine learning algorithms. Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Experience leveraging LLM for specific tasks, e.g. improving data quality or generating explainable text from existing datasets. Business Services ...
For instance, it has the Ask Data feature that allows users to ask questions from any published data source with natural language (via typing) and get answers in the form of a visualization. The feature is based on algorithms “to automatically profile, index, and optimize data sources.”...