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

AltexSoft

OCTOBER 30, 2021

A data scientist takes part in almost all stages of a machine learning project by making important decisions and configuring the model. Data preparation and cleaning. Final analytics are only as good and accurate as the data they use. Managing data and metadata. Providing data access tools.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

ProjectPro

NOVEMBER 15, 2021

In addition to analytics and data science, RAPIDS focuses on everyday data preparation tasks. Delta Lake Source: Github Delta Lake is an open-source project that allows you to create a Lakehouse design based on data lakes. Calcite has chosen to stay out of the data storage and processing business.

Big Data 52

Big Data Project Metadata Programming Language 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

JANUARY 31, 2023

Why is HDFS only suitable for large data sets and not the correct tool for many small files? NameNode is often given a large space to contain metadata for large-scale files. The metadata should come from a single file for optimal space use and economic benefit. Explain the data preparation process.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value.

Engineering 83

Engineering Raw Data Data Science Scala 83

Cloudera

JUNE 4, 2018

The solution to this massive data challenge embedded the Aspire Content Processing Framework into the Cloudera Enterprise Data Hub as a Cloudera Parcel – a binary distribution format containing the program files, along with additional metadata used by Cloudera Manager.

Pharmaceutical 46

Pharmaceutical Unstructured Data Electronics Metadata 46

ProjectPro

AUGUST 24, 2021

In this project, you will explore the usage of Databricks Spark on Azure with Spark SQL and build this data pipeline. Upload it to Azure Data lake storage manually. Create a Data Factory pipeline to ingest files. There are three stages in this real-world data engineering project. The final step is Publish.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

DECEMBER 10, 2021

It specifies who can run the service and also gives users access to built-in data explorer tools. Access Control List - Azure Data Lake Storage determines which data objects users can read, write, or execute. What are the two different types of data flow transformations in Azure Data Factory?

BI 52

BI Cloud Computing SQL Database 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 Government Data Science 52