Data cleansing, data cleaning and data scrubbing are often used interchangeably. For the most part, they're considered to be the same thing. In some cases, though, data scrubbing is viewed as an element of data cleansing that specifically involves removing duplicate, bad, unneeded or old data ...
Another term you might encounter when dealing with data analysis isdata mining– the application of statistical methods to very large and complex datasets with the purpose ofidentifying new patterns. For example, if you want to evaluate the purchasing behavior of certain customer groups, you need t...
Clean data is an ongoing process. Having the right tools in place working as they should, with the ability to grow with your business, solidifies your success strategy. Ensuring you have up-to-date and consistent data will give your team better data-driven insights into what your users need...
Customer data is collected in several ways. It is collected in batches for a period of time and then loaded into the system in a single batch. Batch processing is automated through workflows as a part of a data pipeline. You can also set up incremental batch processing to only bring in t...
where billing is managed by one company and CRM is managed by another company. If the CRM company needs some data from the company that is managing the Billing, then that company will receive a data feed from the other company. To load the data from the feed, an ETL process is used. ...
Unlike data blending, which often involves combining data for immediate analysis, data warehousing provides a structured environment for long-term storage and retrieval of integrated data. Data integration Data integration is the overarching process of combining data from diverse sources to provide a ...
adjusts as it evaluates training data, the process of exposure and calculation around new data trains the algorithm to become better at what it does. The algorithm is the computational part of the project, while the term “model” is a trained algorithm that can be used for real-word use ...
Another common cause of data inaccuracy is the lack of data standardization. This occurs when different departments or groups within an organization use other systems or formats for storing and tracking data. For example,one department might use all uppercase letters while another uses all lowercase...
Graph analytics is another commonly used term, and it refers specifically to the process of analyzing data in a graph format using data points as nodes and relationships as edges. Graph analytics requires a database that can support graph formats; this could be a dedicated graph database, or ...
Data processing Serverless is well suited to working with structured text, audio, image and video data around tasks such as data enrichment, transformation, validation and cleansing. Developers can also use it for PDF processing, audio normalization, image processing (rotation, sharpening, noise reduct...