Cloudera

AUGUST 31, 2021

These schemas will be created based on its definitions in existing legacy data warehouses. Smart DwH Mover helps in accelerating data warehouse migration. Smart Data Validator helps in extensive data reconciliation and testing. Smart Query Convertor converts queries and views to be made compatible on CDW.

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

DataKitchen

SEPTEMBER 21, 2023

L1 is usually the raw, unprocessed data ingested directly from various sources; L2 is an intermediate layer featuring data that has undergone some form of transformation or cleaning; and L3 contains highly processed, optimized, and typically ready for analytics and decision-making processes.

Raw Data 67

Raw Data Data Business Intelligence Data Engineering 67

Ascend.io

JUNE 8, 2023

Acting as the core infrastructure, data pipelines include the crucial steps of data ingestion, transformation, and sharing. Data Ingestion Data in today’s businesses come from an array of sources, including various clouds, APIs, warehouses, and applications.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Databand.ai

AUGUST 30, 2023

Automation plays a critical role in the DataOps framework, as it enables organizations to streamline their data management and analytics processes and reduce the potential for human error. This can be achieved through the use of automated data ingestion, transformation, and analysis tools.

Data Governance 52

Data Governance Data Pipeline Government Business Analyst 52

Knowledge Hut

SEPTEMBER 25, 2023

As an Azure Data Engineer, you will be expected to design, implement, and manage data solutions on the Microsoft Azure cloud platform. You will be in charge of creating and maintaining data pipelines, data storage solutions, data processing, and data integration to enable data-driven decision-making inside a company.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Processing: This is the final step in deploying a big data model.

Big Data 52

Big Data Hadoop Relational Database AWS 52

phData: Data Engineering

JANUARY 3, 2022

This allows us to create new versions of our data sets, populate them with data, validate our data, and then redeploy our views on top of that data to use the new version of our data. This proactive approach to data validation allows you to minimize risks and get ahead of the issue.

IT 52

IT AWS Software Engineer Software Engineering 52

ProjectPro

AUGUST 21, 2015

Big Data Hadoop Interview Questions and Answers These are Hadoop Basic Interview Questions and Answers for freshers and experienced. Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. More data needs to be substantiated.

Hadoop 40

Hadoop Big Data Metadata Java 40

Striim

AUGUST 28, 2024

These roles will span various sectors, including data science, AI ethics, machine learning engineering, and AI-related research and development. Real-Time Data — The Missing Link What is Real-Time Data? Misconception: Batch Processing Suffices Objection: Many AI/ML tasks can be handled with batch processing.

Healthcare 96

Healthcare Retail Algorithm Finance 96

Striim

JUNE 17, 2024

These roles will span various sectors, including data science, AI ethics, machine learning engineering, and AI-related research and development. Real-Time Data — The Missing Link What is Real-Time Data? ” Complexity and Cost Objection: Implementing real-time data systems is complex and costly.

Algorithm 52

Algorithm Retail Data Ingestion Healthcare 52