Edureka

JULY 16, 2024

Machine Learning in AWS SageMaker Machine learning in AWS SageMaker involves steps facilitated by various tools and services within the platform: Data Preparation: SageMaker comprises tools for labeling the data and data and feature transformation. This ensures that the data is secured from its generation to its disposal.

AWS 52

AWS Algorithm Machine Learning Amazon Web Services 52

Cloudera

MARCH 31, 2021

Customers who have chosen Google Cloud as their cloud platform can now use CDP Public Cloud to create secure governed data lakes in their own cloud accounts and deliver security, compliance and metadata management across multiple compute clusters. Data Preparation (Apache Spark and Apache Hive) .

Google Cloud 99

Google Cloud Cloud Amazon Web Services Cloud Storage 99

ProjectPro

JANUARY 19, 2022

ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse. Different methods are used to store different types of data. It is better to know when to employ a data lake vs. a data warehouse to create data solutions for an organization.

Data Engineer 52

Data Engineer Data Engineering Engineering Scala 52

Cloudera

DECEMBER 16, 2022

Cloudera has long had the capabilities of a data lakehouse, if not the label. Cloudera enables an open data lakehouse architecture that combines all the flexibility of the data lake with the performance of the data warehouse, so enterprises can use all data — both structured and unstructured.

Database 96

Database Cloud Systems Management 96

Edureka

FEBRUARY 7, 2023

Dynamic data masking serves several important functions in data security. It can be set up as a security policy on all SQL Databases in an Azure subscription. One can use polybase: From Azure SQL Database or Azure Synapse Analytics, query data kept in Hadoop, Azure Blob Storage, or Azure Data Lake Store.

Data Engineer 52

Data Engineer Data Engineering Engineering Hadoop 52

ProjectPro

JANUARY 31, 2022

It also offers a unique architecture that allows users to quickly build tables and begin querying data without administrative or DBA involvement. Snowflake is a cloud-based data platform that provides excellent manageability regarding data warehousing, data lakes, data analytics, etc. What Does Snowflake Do?

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

NOVEMBER 15, 2021

In addition to analytics and data science, RAPIDS focuses on everyday data preparation tasks. It offers a fault-tolerant storage engine that prioritizes data security. Delta Lake Source: Github Delta Lake is an open-source project that allows you to create a Lakehouse design based on data lakes.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

OCTOBER 20, 2021

This would include the automation of a standard machine learning workflow which would include the steps of Gathering the data Preparing the Data Training Evaluation Testing Deployment and Prediction This includes the automation of tasks such as Hyperparameter Optimization, Model Selection, and Feature Selection.

Machine Learning 52

Machine Learning Algorithm Data Science Government 52

Edureka

JULY 4, 2024

On the other hand, thanks to the Spark component, you can perform data preparation, data engineering, ETL, and machine learning tasks using industry-standard Apache Spark. You can be confident about your data security with features like column-level security, dynamic data masking, and automated threat detection.

Data Lake 40

Data Lake Pipeline-centric Scala Data Warehouse 40

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64