Data applications are applications built on top of databases that solve a niche data problem and, by means of a visual interface, allow for multiple queries at the same time to explore and interact with that data. Data applications do not require coding knowledge in order to procure or understand ...
Data enrichment is the process of combining first party data from internal sources with disparate data from other internal systems or third party data from external sources. The data enrichment process makes data more useful and insightful. A well-functioning data enrichment process is a fundamen ...
Data exploration is one of the initial steps in the analysis process that is used to begin exploring and determining what patterns and trends are found in the dataset. An analyst will usually begin data exploration by using data visualization techniques and other tools to describe the characteris ...
Data governance is the collection of policies, processes and standards that define how data assets can be used within an organization and who has authority over them. Governance dictates who can use what data and in what way. This ensures that data assets remain secure and adhere to agreed upon q ...
Batch processing refers to the scheduling and processing of large volumes of data simultaneously, generally at periods of time when computing resources are experiencing low demand. Batch jobs are typically repetitive in nature and are often scheduled (automated) to occur at set intervals, such as ...
Data munging is the process of manual data cleansing prior to analysis. It is a time consuming process that often gets in the way of extracting true value and potential from data. In many organizations, 80% of the time spent on data analytics is allocated to data munging, where IT manually cleans ...
Data onboarding is the process of preparing and uploading customer data into an online environment. It allows organizations to bring customer records gathered through offline means into online systems, such as CRMs. Data onboarding requires significant data cleansing to correct for errors and for ...
A data pipeline is a sequence of steps that collect, process, and move data between sources for storage, analytics, machine learning, or other uses. For example, data pipelines are often used to send data from applications to storage devices like data warehouses or data lakes. Data pipelines are ...
Data transformation is the process of converting data into a different format that is more useful to an organization. It is used to standardize data between data sets, or to make data more useful for analysis and machine learning. The most common data transformations involve converting raw data i ...
A regex (short for regular expression) is a sequence of characters used to specify a search pattern. It allows users to easily conduct searches matching very specific criteria, saving large amounts of time for those who regularly work with text or analyze large volumes of data. An example of a re ...
A User Defined Function (UDF) is a custom programming function that allows users to reuse processes without having to rewrite code. For example, a complex calculation can be programmed using SQL and stored as a UDF. When this calculation needs to be used in the future on a different set of data, ...
Data aggregation is the process of compiling data (often from multiple data sources) to provide high-level summary information that can be used for statistical analysis. An example of a simple data aggregation is finding the sum of the sales in a particular product category for each region you op ...
A cloud data warehouse is a database that is managed as a service and delivered by a third party, such as Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure. Cloud data architectures are distinct from on-premise data architectures, where organizations manage their own phys ...