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

In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers. After navigating the complexity of multiple systems and stages to bring data to its end-use case, the final product’s value becomes the ultimate yardstick for measuring success.

Raw Data 69

Raw Data Data Business Intelligence Data Engineering 69

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

Monte Carlo

JULY 10, 2023

Data can go missing for nearly endless reasons, but here are a few of the most common challenges around data completeness: Inadequate data collection processes Data collection and data ingestion can cause data completion issues when collection procedures aren’t standardized, requirements aren’t clearly defined, and fields are incomplete or missing.

Data Collection 40

Data Collection Data Governance Government Data 40

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. Enriching data entails connecting it to other related data to produce deeper insights.

Big Data 52

Big Data Hadoop Relational Database AWS 52

ProjectPro

AUGUST 21, 2015

Core components of a Hadoop application are- 1) Hadoop Common 2) HDFS 3) Hadoop MapReduce 4) YARN Data Access Components are - Pig and Hive Data Storage Component is - HBase Data Integration Components are - Apache Flume, Sqoop, Chukwa Data Management and Monitoring Components are - Ambari, Oozie and Zookeeper.

Hadoop 40

Hadoop Big Data Metadata Java 40

Striim

AUGUST 28, 2024

The necessity of real-time data is highly specific to certain use cases, and not all industries or applications benefit equally. Real-time data integration allows models to process the most recent data points, reducing lag between data generation and actionable insights.

Healthcare 96

Healthcare Retail Algorithm Finance 96

Striim

JUNE 17, 2024

Real-time data integration allows models to process the most recent data points, reducing lag between data generation and actionable insights. The notion that real-time data is only useful in specific cases is outdated as countless industries increasingly leverage real-time capabilities to stay competitive and responsive.”

Algorithm 52

Algorithm Retail Data Ingestion Healthcare 52

Snowflake

NOVEMBER 19, 2024

How Snowflake can help: Snowflake offers a variety of options for data ingestion. Additionally, Snowflake’s robust data integration ecosystem tools enable secure and controlled incremental uploads without the need for complex infrastructure. For real-time, continuous loading, Snowpipe is ideal for trickle feeds.

Cloud 98

Cloud Data Ingestion Data Validation Data Security 98