Data Engineering Podcast

JUNE 12, 2022

Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value. Unstruk is the DataOps platform for your unstructured data.

Metadata 100

Metadata Unstructured Data Business Intelligence MongoDB 100

Striim

OCTOBER 11, 2024

Then, we’ll explore a data pipeline example and dive deeper into the key differences between a traditional data pipeline vs ETL. What is a Data Pipeline? A data pipeline refers to a series of processes that transport data from one or more sources to a destination, such as a data warehouse, database, or application.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Data Engineering Podcast

JULY 3, 2022

Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value. Tired of deploying bad data? Tired of deploying bad data?

Architecture 100

Architecture Metadata MongoDB MySQL 100

Striim

SEPTEMBER 11, 2024

The approach to this processing depends on the data pipeline architecture, specifically whether it employs ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes. This method is advantageous when dealing with structured data that requires pre-processing before storage. In what format will the final data be stored?

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Data Engineering Podcast

JULY 17, 2022

Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value. Tired of deploying bad data? Tired of deploying bad data?

Data Management 130

Data Management Management Metadata MongoDB 130

Data Engineering Podcast

JULY 10, 2022

Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value. Tired of deploying bad data? Tired of deploying bad data?

Metadata 100

Metadata MongoDB MySQL Data Pipeline 100

Data Engineering Podcast

JUNE 5, 2022

Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value. Data teams are increasingly under pressure to deliver.

Data Security 100

Data Security Metadata MongoDB Scala 100

Data Engineering Podcast

DECEMBER 21, 2020

Fortunately, there’s hope: in the same way that New Relic, DataDog, and other Application Performance Management solutions ensure reliable software and keep application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. The first 25 will receive a free, limited edition Monte Carlo hat!

Data Governance 130

Data Governance Government Data Lake Banking 130

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 80

Data Warehouse Database-centric Metadata Cloud 80

Data Engineering Podcast

OCTOBER 9, 2018

Summary One of the most complex aspects of managing data for analytical workloads is moving it from a transactional database into the data warehouse. Request a demo at dataengineeringpodcast.com/metis-machine to learn more about how Metis Machine is operationalizing data science.

PostgreSQL 100

PostgreSQL BI Machine Learning Data Warehouse 100

Cloudera

FEBRUARY 8, 2024

Apache Iceberg forms the core foundation for Cloudera’s Open Data Lakehouse with the Cloudera Data Platform (CDP). Materialized views are valuable for accelerating common classes of business intelligence (BI) queries that consist of joins, group-bys and aggregate functions. Starting from the CDW Public Cloud DWX-1.6.1

Metadata 89

Metadata Data Warehouse BI AWS 89

Data Engineering Podcast

JANUARY 11, 2021

Fortunately, there’s hope: in the same way that New Relic, DataDog, and other Application Performance Management solutions ensure reliable software and keep application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. The first 25 will receive a free, limited edition Monte Carlo hat!

PostgreSQL 100

PostgreSQL Python Computer Science Data Lake 100

Data Engineering Podcast

SEPTEMBER 3, 2018

Using master data management to build a data catalog helps you answer these questions reliably and simplify the process of building your business intelligence reports. Request a demo at dataengineeringpodcast.com/metis-machine to learn more about how Metis Machine is operationalizing data science.

Data Management 100

Data Management Management Relational Database Business Intelligence 100

Data Engineering Podcast

JANUARY 4, 2021

Fortunately, there’s hope: in the same way that New Relic, DataDog, and other Application Performance Management solutions ensure reliable software and keep application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. The first 25 will receive a free, limited edition Monte Carlo hat!

Python 100

Python Machine Learning Computer Science Data Lake 100

Ascend.io

OCTOBER 28, 2024

Data Aggregation Data aggregation is a powerful technique that involves compiling data from various sources to provide a comprehensive view. This process is crucial for generating summary statistics, such as averages, sums, and counts, which are essential for business intelligence and analytics.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Striim

FEBRUARY 10, 2023

To facilitate the data integration process, it used Striim, which allowed it to: Import historical and real-time on-premise data from its Oracle and DB2 mainframe databases. Process the data in flight, including detecting and transforming mismatched timestamp fields. Request a demo today.

Data Analytics 52

Data Analytics Telecommunication Insurance Google Cloud 52

Monte Carlo

JANUARY 29, 2021

They needed a way to automatically identify, resolve, and prevent data quality issues before they affected the business – in other words, they needed data observability. Request a free trial!

Business Intelligence 40

Business Intelligence Data Warehouse Data Pipeline Data 40

Monte Carlo

APRIL 4, 2023

The integration with Fivetran is the latest step in Monte Carlo’s mission to bring end-to-end data observability for customers across their data stack. The announcement was made at the Modern Data Stack Conference , the annual conference organized and hosted by Fivetran.

ETL Tools 52

ETL Tools Data Pipeline Business Intelligence Data Warehouse 52

Monte Carlo

APRIL 4, 2023

The integration with Fivetran is the latest step in Monte Carlo’s mission to bring end-to-end data observability for customers across their data stack. The announcement was made at the Modern Data Stack Conference , the annual conference organized and hosted by Fivetran.

ETL Tools 52

ETL Tools Data Pipeline Business Intelligence Data Warehouse 52

The Modern Data Company

MARCH 23, 2023

However, to unlock the maximum power of corporate data, it is necessary to mix data from different systems and allow each data source to enhance the others. Various architectures, from data warehouses to data lakes, have attempted to help solve this problem over the years.

Data Lake 95

Data Lake Data Warehouse Architecture Systems 95

Cloudera

DECEMBER 10, 2020

Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If not, before adopting a cloud data warehouse, consider the true costs of a cloud-native data warehouse. These costs impede the adoption of cloud-native data warehouses.

Data Warehouse 98

Data Warehouse Cloud Storage Metadata Data 98

Striim

AUGUST 22, 2024

Streaming analytics focuses on analyzing data in motion, unlike traditional analytics, which deals with data stored in databases or data warehouses. Extract insights by analyzing data Finally, your team will extract actionable insights. Ready to discover how Striim can help evolve how you process data?

Data Warehouse 52

Data Warehouse Retail Machine Learning Database 52

Rockset

FEBRUARY 24, 2022

Elasticsearch Summary Elasticsearch is a popular tool for achieving full-text search, especially for log analytics, but is less useful as a fully-featured analytics engine for events data. Redshift Amazon Redshift is a high performance, massively parallel processing (MPP) data warehouse designed for query latencies of second/minutes.

AWS 52

AWS Amazon Web Services Kafka SQL 52

Monte Carlo

JULY 13, 2021

Incident IQ is the first fully automated, end-to-end solution that conducts root cause analysis for data issues and changes at each stage of the pipeline, from ingestion in the data warehouse or lake to analytics in your business intelligence dashboards. EST / 9:00 a.m. PST to learn more.

Food 40

Food Data Pipeline BI Business Intelligence 40

AltexSoft

OCTOBER 8, 2021

Data integration defines the process of collecting data from a number of disparate source systems and presenting it in a unified form within a centralized location like a data warehouse. So, why is data integration such a big deal? Oracle Data Integrator, IBM InfoSphere, Snaplogic, Xplenty, and.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

Monte Carlo

JULY 13, 2021

To help companies eliminate data downtime, Monte Carlo built Incident IQ, the first end-to-end data incident management solution that conducts root cause analysis for data issues at each stage of the pipeline, from ingestion in the data warehouse or lake to analytics in your business intelligence dashboards.

Management 40

Management Data Pipeline Retail BI 40

AltexSoft

SEPTEMBER 10, 2021

Data integration is the process of taking data from multiple disparate internal and external sources and putting it in a single location (e.g., data warehouse ) to achieve a unified view of collected data. So, why does anyone need to integrate data in the first place? Key types of data integration.

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

Cloudera

SEPTEMBER 12, 2018

Connecting internal, external and unconventional data (such as sensor and video data) helps the organization create an end-to-end product performance strategy, while common governance and security enable self-service capabilities for business users. Modern Data Warehousing: Barclays (nominated together with BlueData ).

Pharmaceutical 44

Pharmaceutical Banking Amazon Web Services Machine Learning 44

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

phData: Data Engineering

DECEMBER 20, 2022

Congratulations—at last, you’ve finished your cloud data migration and it feels as if you just bought a brand new car! Hopefully, your cutting-edge cloud data warehouse comes with the latest and greatest safety features, too. To see Anomalo for yourself, request a demo today. You can go from 0 to 60 in how many seconds?

Cloud 52

Cloud Database-centric Data Data Warehouse 52

Monte Carlo

APRIL 20, 2023

Solutions with automated data lineage capabilities constantly update these graphs and illustrate them as nodes and edges, or in other words, the objects through which the data travels and the relationship between them. This is one of the most frequent data lineage use cases leveraged by Vox. Data lineage can help!

Data Warehouse 52

Data Warehouse BI Data Government 52

Monte Carlo

SEPTEMBER 8, 2021

Modern data teams have all the right solutions in place to ensure that data is ingested, stored, transformed, and loaded into their data warehouse, but what happens at “the last mile?” In other words, how can data analysts and engineers ensure that transformed, actionable data is actually available to access and use?

ETL Tools 52

ETL Tools Data Warehouse BI Data Pipeline 52