Regex in Alteryx | Explained & Use Cases
A regular expression (regex) is a sequence of characters that specify or define a search pattern in text. Alteryx makes it an easy task.
A regular expression (regex) is a sequence of characters that specify or define a search pattern in text. Alteryx makes it an easy task.
Meta data describes and contextualises the data that it accompanies. It’s essential for understanding and managing the data it describes.
Data mesh is a type of data platform architecture and strategic framework that aims to make data accessible and readily available to business users.
With effective Data Governance, companies are better positioned to defend themselves from cyber-attacks, because they know where their most valuable data is. Billigence recently explored this topic with Collibra’s Co-founder and Chief Data Citizen, Stijn Christiaens.
AutoML is the process of applying machine learning models to real-world problems using automation. More specifically, it automates the selection and parameterisation of machine learning models, which can be time consuming and tedious. Alteryx AutoML is a cloud-native tool that enables users to prepare, blend and output data without having to write any lines of code.
Collibra Protect for Snowflake is a data access governance solution that allows users to create code-free policies for data stored in Snowflake’s Data Cloud. Automated Policy creation ensures sensitive data and PI is protected, instilling trust and confidence in the data and its security.
To best achieve competitive advantage, AIS partnered with Billigence, experts in Business Intelligence and Data Analytics to build a cloud-native, scalable and secure data environment that could deliver powerful insights through a data science driven approach.
On-premise data warehouses are large, costly, inflexible and require constant upkeep, that’s why most businesses are moving to data clouds. We’ve been helping our clients transition for years and we anticipate these projects increasing tenfold as the industry accepts clouds for what they are – easy, secure, scalable and cost-effective.
On-premise data warehouses are large, costly, inflexible and require constant upkeep, that’s why most businesses are moving to data clouds. We’ve been helping our clients transition for years and we anticipate these projects increasing tenfold as the industry accepts clouds for what they are – easy, secure, scalable and cost-effective.
Data can only be used to generate accurate insights when it’s properly formatted and cleaned thoroughly. Therefore, the data cleansing and preparation process is a very crucial step to ensure good data hygiene as well as accuracy.