Terminology
Self-service analytics empower non-technical teams to interact with data, perform queries, and glean helpful business insights.
Terminology
Data sovereignty defines the regulations data is subject to. Fortunately, there are actionable steps brands can take to ensure compliance.
Terminology
Time-series data analysis serves critical functions in most modern industries, and is a powerful method to glean accurate analysis.
Terminology
An EDW is a database that centralizes data from across the business so it can be analyzed and used in decision making.
Terminology
Data platforms are tools that allow businesses to collect, analyze, and present data.
Terminology
When building a database, all data requires some description to help identify its uniqueness, which is where metadata comes in.
Terminology
An ad hoc query is any kind of question you can ask a data system off the top of your head.
Terminology
A query is a question or request for a database written in a code the database can understand, in order to retrieve or modify the correct information.
Terminology
Unlike row-based formats such as CSV, Parquet is a columnar data file storage format.
Terminology
Apache Hadoop is one of the most widely used open source frameworks designed to address the problem of storing and processing big data.
Terminology
Data governance allows organizations to ensure high-quality data through formalized processes for management, monitoring, and control of data assets.
Terminology
ETL is a method to collect raw data from various sources, clean it up, and translate it so it can be used to inform decision making.
Terminology
Lambda architecture processes data through a hybrid combination of batch processing and stream processing.
Terminology
Data lakes and data warehouses are both commonly used for storing data, but there are key differences between the two that make them unique in their own way. Learn which fits your business purposes best and if there is a better solution.
Terminology
The term “data ecosystem” collectively refers to all the programming languages, algorithms, applications, and the general infrastructure used to collect, analyze and store data.
Terminology
Data modeling is a means of creating a conceptual framework for your data in preparation for storage in a data warehouse. The resulting model is a visual representation of the data which maps out the relationships between data, and the rules.
As AI, IoT, and data privacy regulations continue to evolve, there is tremendous potential for consumer-focused industries to transform the way they interact with customers. In a privacy-first DX 2.0 economy, a brand's success depends on its ability to quickly generate comprehensive 360° customer profiles, analyze data from multiple channels, and deliver dynamic and hyper-personalized experiences in real-time.
The future of privacy compliance is still in limbo, but one to keep tabs on. President Biden’s recent executive order may have laid the framework for a new era of transatlantic privacy compliance, but it will likely be several months before the framework receives EU regulator approval, let alone the enviable legal challenges to follow. In the meantime, the stakes have never been higher for transatlantic brands.
Customer data platforms (CDPs) help businesses aggregate and analyze customer data from multiple channels. As brands interact with consumers through various touchpoints, the CDP cleans and unifies the data to build more complete customer profiles. But getting a true 360° view of user behavior remains a challenge.
Time-series data is everywhere—whether or not your brand is equipped to handle it. Data-driven organizations need time-series analysis platforms to make the most of their data, but some brands may not realize there are different techniques for achieving time-series analysis. The question isn’t whether time-series analytics platforms are worth it—they are—but knowing which analysis technique is best suited for your brand goals and needs.
Learn how Bleacher Report uses Scuba to rapidly gain insights into user behavior, increase conversion and engagement, build satisfaction, and redesign their web and mobile applications.
Learn how Scuba is helping Edmunds enable self-service analytics for business users, analysts and executives - faster than complex SQL-based queries.
One of the largest telecomms in the world set an ambitious goal – to dramatically improve their customer experience. They wanted a real time customer experience analytics solution to tackle changing consumer demands and growing competitive pressures.