Slack is a messaging platform for organizations. Since its creation in 2013, Slack has quickly become a core piece of technology used by a wide variety of technology companies, groups, and small teams.  The messages that are sent on Slack are generated at a very high volume, and are extremely sensitive. These messages must be

NoSQL databases provide an interface for storing and accessing data that allows the user to work with data in an “unstructured” fashion. SQL databases require the data in the database to be “normalized,” meaning that each object in the entire database has an entry (or a null value) for each field. One advantage of NoSQL

Relational databases provide durable transactional systems for storing data. The relational model has existed for decades, but the requirements for a relational database have changed. Modern applications have requirements for high volumes of data that do not fit onto a single machine. When a database gets too big to fit on a single machine, that

Machine learning is widely understood by the software community. But it is still hard to build a company around machine learning, because there is not easy access to large, unique data sets. Scale is a platform for training and validating data that is used for machine learning. Most machine learning models are built with supervised

Databases go offline. Services fail to scale up. Deployment errors can cause an application backend to get DDoS’d. When an event happens that prevents your company from operating as expected, it is known as an incident. Software teams respond to an incident by issuing a fix. Sometimes that fix returns the software to its ideal

Data visualization is the presentation of data in a way that emphasizes certain qualities about that data. Data visualization can be used to prove a specific point, or it can be used as a depiction of a data set to be explored. Data visualization is used in consumer software products as well as backend engineering

Data privacy policies have changed how software organizations need to operate. As consumer preferences have shifted in favor of strong privacy, software companies are having to examine their policies around data collection and retention. Many software companies were started in a time with different norms around data.  Building a new application that is compliant with

Large companies have multiple databases, multiple data formats, and multiple applications that need to use the data. Every data engineer needs to move data between these different components of a system. Moving data between different parts of a system is often called “ETL”, an acronym for “Extract, Transform, Load.” Data engineers spend much of their

Ethos Life Insurance is a software company that sells life insurance products. Software is reshaping established industries such as banking, insurance, and manufacturing. In these large, established industries, incumbents are adopting new technology as fast as they can, but the new technology needs to be integrated with the old technology. The slow rate of technology

A new software product usually starts with a single database. That database manages the tables for user accounts and basic transactions. When a product becomes popular, the database grows in size. There are more transactions and more users. A company grows around that product, and the company starts to accumulate more data in different sources.