Towards Data Science

NOVEMBER 4, 2023

Indeed, datalakes can store all types of data including unstructured ones and we still need to be able to analyse these datasets. What I like about it is that it makes it really easy to work with various data file formats, i.e. SQL, XML, XLS, CSV and JSON. You can change these # to conform to your data. Datalake example.

Data Engineering 79

Data Engineering Data Engineer Engineering BI 79

ProjectPro

FEBRUARY 8, 2023

AWS Glue then creates data profiles in the catalog, a repository for all data assets' metadata, including table definitions, locations, and other features. Let us look at some significant reasons that make AWS Glue a popular serverless data integration service across organizations worldwide. Why Use AWS Glue?

AWS 98

AWS Scala Metadata Data Lake 98

Towards Data Science

MARCH 9, 2023

Although within a big data context, Apache Spark’s MLLib tends to overperform scikit-learn due to its fit for distributed computation, as it is designed to run on Spark. Datasets containing attributes of Airbnb listings in 10 European cities ¹ will be used to create the same Pipeline in scikit-learn and MLLib. Source: The author.

Machine Learning 72

Machine Learning Building Datasets Scala 72

Monte Carlo

FEBRUARY 26, 2024

Data catalogs are important because they allow users of varying types to access useful data quickly and effectively and can help team members collaborate and maintain consistent organization-wide data definitions. Governance can be handled at a granular level and access control becomes part of the custom workflow.

Metadata 52

Metadata Government Data Data Governance 52

Striim

NOVEMBER 8, 2023

Data Mesh is a revolutionary event streaming architecture that helps organizations quickly and easily integrate real-time data, stream analytics, and more. It enables data to be accessed, transferred, and used in various ways such as creating dashboards or running analytics.

Architecture 52

Architecture Generalist Government Datasets 52

Pinterest Engineering

MAY 2, 2023

We set up a separate dataset for each event type indexed by our system, because we want to have the flexibility to scale these datasets independently. In particular, we wanted our KV store datasets to have the following properties: Allows inserts. We need each dataset to store the last N events for a user.

Lambda Architecture 66

Lambda Architecture Datasets Software Engineer Software Engineering 66

Rockset

OCTOBER 6, 2022

Consequently, we needed a data backend with the following characteristics: Scale With ~50 commits per working day (and thus at least 50 pull request updates per day) and each commit running over one million tests, you can imagine the storage/computation required to upload and process all our data.

AWS 52

AWS Data Schemas Accessible Accessibility 52