List Categories and Listings by D

Data Science Notebooks are interactive computing environments that allow data scientists and analysts to work with data, perform data analysis, and create visualizations, all within a single platform. They provide an integrated environment for programming ...

Data + AI Summit is an annual conference organized by Databricks that brings together data scientists, engineers, and business leaders to share their knowledge and experiences in data science, artificial intelligence (AI), and big data technologies. Th ...

A Data Analyst is responsible for collecting, analyzing, and interpreting large sets of data and turning them into actionable insights. What does the role involve? Data Analysts' role involves cleaning and organizing data, developing data models ...

Data warehousing is the process of centralizing, storing, and integrating large volumes of structured and semi-structured data in a single location, in order to enable data analysis and reporting. A data warehouse is a specialized database designed to sup ...

A data attribute is a characteristic or property of a data entity, such as a person, place, thing, or event. It provides additional information about the entity and helps to distinguish it from other entities. For example, in a database of customer inf ...

A Data Engineer is responsible for building and maintaining the data infrastructure of an organization. The role of a Data Engineer involves designing, developing, and maintaining the data architecture, data pipelines, and data warehouse systems that enab ...

A Data Analytics Manager is a professional responsible for overseeing the data analytics activities within an organization. Their primary role is to manage and lead a team of data analysts to gather, process, analyze, and interpret data in order to provid ...

A Data Architect is responsible for designing and maintaining an organization's data architecture to support business requirements and enable efficient data processing, storage, and retrieval. Their role involves working with various stakeholders in the o ...

A Data Developer is responsible for designing, developing, and implementing data processing systems and solutions to support an organization's data needs. Their role involves working closely with data architects, data scientists, and business analysts to ...

A Data Scientist is a professional who collects, analyzes, and interprets large sets of complex data using statistical and machine learning techniques. Their role involves working with raw data to develop predictive models, identify patterns and insights, ...

A Data Governance Specialist is a professional responsible for ensuring that an organization's data is managed in a way that meets regulatory requirements, industry standards, and best practices. They work closely with various stakeholders across the orga ...

Data classification is the process of organizing and categorizing data based on its sensitivity, value, or other criteria. The goal of data classification is to ensure that data is protected and handled appropriately based on its level of sensitivity or i ...

A Data Engineering Manager is responsible for managing the development, deployment, and maintenance of large-scale data processing systems. Their role involves leading a team of data engineers to design and implement data pipelines, data warehouses, and d ...

Data governance is the process of managing the availability, usability, integrity, and security of data used in an organization. It involves establishing policies, procedures, and standards for acquiring, storing, protecting, processing, and distributing ...

A Data Modeller is a professional responsible for creating and maintaining data models for an organization. Data models are diagrams or descriptions that represent an organization's data in a structured way, showing the relationships between different typ ...

Data integration is the process of combining data from multiple sources into a single, unified view, which can be used for analysis, decision-making, and other business purposes. Data integration involves the following steps: Data Collection: Data is c ...

Data provenance refers to the record of the origin, ownership, custody, and processing history of a piece of data, as well as any changes or transformations it has undergone. It is essentially the history of the data, including information about who creat ...

Data lineage refers to the journey of data from its origin to its destination, including all the transformations and processing that it undergoes along the way. It is the process of tracking data movement and changes as it flows through various systems, a ...

Data traceability is the ability to trace the movement of data throughout its lifecycle, including its origin, transformation, and consumption. It involves recording and tracking the history of data elements, including their metadata, across systems and p ...

Data architecture refers to the design and organization of data systems, including data models, databases, data warehouses, and other data repositories. The goal of data architecture is to ensure that data is organized, structured, and stored in a way tha ...