Data Engineering Podcast

JULY 10, 2022

They also discuss how they have established a guild system for training and supporting data professionals in the organization. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Tired of deploying bad data? What does Riskified do?

Metadata 100

Metadata MongoDB MySQL Data Pipeline 100

Data Engineering Podcast

APRIL 24, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. Missing data?

Data Warehouse 100

Data Warehouse Data Lake Data Pipeline BI 100

Data Engineering Podcast

DECEMBER 21, 2020

If you are starting down the path of implementing a data governance strategy then this episode will provide a great overview of what is involved. If you hand a book to a new data engineer, what wisdom would you add to it? What is data governance? If you hand a book to a new data engineer, what wisdom would you add to it?

Data Governance 130

Data Governance Government Data Lake Banking 130

Data Engineering Podcast

JULY 3, 2022

She also discusses her views on the role of the data lakehouse as a building block for these architectures and the ongoing influence that it will have as the technology matures. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows.

Architecture 100

Architecture Metadata MongoDB MySQL 100

Data Engineering Podcast

JANUARY 4, 2021

Summary As more organizations are gaining experience with data management and incorporating analytics into their decision making, their next move is to adopt machine learning. Monte Carlo’s end-to-end Data Observability Platform monitors and alerts for data issues across your data warehouses, data lakes, ETL, and business intelligence.

Python 100

Python Machine Learning Computer Science Data Lake 100

Data Engineering Podcast

SEPTEMBER 16, 2018

Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline you’ll need somewhere to deploy it, so check out Linode. What is unique about customer event data from an ingestion and processing perspective?

Google Cloud 100

Google Cloud Hadoop Business Intelligence Consulting 100

Data Engineering Podcast

JANUARY 11, 2021

This is a fascinating conversation on the technical challenges involved, the opportunities that such as system provides, and the complexities inherent to building a successful business on open source. There are a number of different reasons and methods for versioning data, such as the work being done with Datomic, LakeFS, DVC, etc.

PostgreSQL 100

PostgreSQL Python Computer Science Data Lake 100

Data Engineering Podcast

OCTOBER 9, 2018

This was a deep dive on how to build a successful company around a powerful platform, and how that platform simplifies operations for enterprise grade data management. 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

Monte Carlo

JULY 15, 2024

In this post, we’ll dive into the world of data ownership, exploring how this new breed of professionals is shaping the future of business intelligence and why, in the coming years, the success of your data strategy may hinge on the effectiveness of your data owners. Table of Contents What is a Data Owner?

Pipeline-centric 52

Pipeline-centric Government Data Governance Retail 52

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

OCTOBER 11, 2024

Change Data Capture (CDC) plays a key role here by capturing and streaming only the changes (inserts, updates, deletes) in real time, ensuring efficient data handling and up-to-date information across systems. As a result, stream processing makes real-time business intelligence feasible.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Striim

FEBRUARY 10, 2023

Macy’s migrated its on-premise inventory and order data to Google Cloud storage to reach its objectives. The company decided to move to the cloud based on the benefits of cost efficiency, flexibility, and improved data management. Help customers visualize their data using a business intelligence tool.

Data Analytics 52

Data Analytics Telecommunication Insurance Google Cloud 52

The Modern Data Company

JANUARY 31, 2023

We also had the opportunity to talk about DataOS and the new paradigm it presents to the world of data. Our founders — and, as a result, the entire company — think about data differently than everyone else. Schedule a demo and see it all for yourself. Eager to get started?

Retail 98

Retail Healthcare Data Architecture Data Pipeline 98

Monte Carlo

MAY 25, 2023

By dramatically improving visibility across data operations and streamlining communication, thereby enabling wider trust in data, data consumers and engineers can work with data in more efficient, collaborative, and innovative ways.

Metadata 52

Metadata Data Governance Government Business Intelligence 52

Cloudera

AUGUST 31, 2021

Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis. Demo Video. Copyright © 2021 Accenture. Solution brief.

Data Warehouse 81

Data Warehouse Database-centric Metadata Cloud 81

Striim

SEPTEMBER 11, 2024

Data Warehouses: These are optimized for storing structured data, often organized in relational databases. They support complex querying and analytical processing, making them ideal for business intelligence and reporting. Schedule a demo today to discover how Striim can transform your data management strategy.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

AltexSoft

OCTOBER 8, 2021

The bad news is, integrating data can become a tedious task, especially when done manually. Luckily, there are various data integration tools that support automation and provide a unified data view for more efficient data management. Data integration process. Here, we’ll be comparing such vendors as.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

Monte Carlo

FEBRUARY 6, 2023

How should your business intelligence improve as a result of this migration? Set your budget While you’ll likely save on a data warehouse migration to cloud tooling, the migration process will create costs of its own. Interested in learning about how data observability can simplify your data warehouse migration?

Data Warehouse 52

Data Warehouse AWS Data Validation Data 52

AltexSoft

SEPTEMBER 10, 2021

So, why does anyone need to integrate data in the first place? Today, companies want their business decisions to be driven by data. But here’s the thing — information required for business intelligence (BI) and analytics processes often lives in a breadth of databases and applications. Middleware data integration.

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

Cloudera

SEPTEMBER 12, 2018

It’s a big week for us, as many Clouderans descend on New York for the Strata Data Conference. The week is typically filled with exciting announcements from Cloudera and many partners and others in the data management, machine learning and analytics industry. Kar Leong Tew , Research Manager, IDC, @KarLeongTew.

Pharmaceutical 45

Pharmaceutical Banking Amazon Web Services Machine Learning 45

ProjectPro

MAY 20, 2015

CRN editorial team, has appreciated this challenge taken up by various big data companies and identified the best big data and business analytics companies that are innovating out-of-the-box data management, business analytics and infrastructure services and technologies in the big data market.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

The Modern Data Company

JANUARY 22, 2024

The Modern Story: Navigating Complexity and Rethinking Data in The Business Landscape Enterprises face a data landscape marked by the proliferation of IoT-generated data, an influx of unstructured data, and a pervasive need for comprehensive data analytics.

Data Integration 98

Data Integration Metadata Government Unstructured Data 98

The Modern Data Company

JANUARY 22, 2024

The Modern Story: Navigating Complexity and Rethinking Data in The Business Landscape Enterprises face a data landscape marked by the proliferation of IoT-generated data, an influx of unstructured data, and a pervasive need for comprehensive data analytics.

Data Integration 87

Data Integration Metadata Government Unstructured Data 87

The Modern Data Company

APRIL 20, 2023

On the surface, it’s an operating system designed specifically for managing and processing large amounts of data. It typically provides a scalable and flexible infrastructure for storing, processing, and analyzing big data and should also include features that support data management, data protection, and data governance.

Systems 95

Systems Entertainment Government Big Data 95

phData: Data Engineering

DECEMBER 20, 2022

In contrast, a cloud provider specializes in data infrastructure, typically offers multiple back-ups to reduce the risk of outages, and abstracts away any thought you have to give to data management—it just works. The cloud also democratizes access to data, whereas on-premises databases tend to restrict access and create silos.

Cloud 52

Cloud Database-centric Data Data Warehouse 52

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

Monte Carlo

APRIL 20, 2023

Overwhelmed data engineers need to have the proper context of the blast radius to understand which incidents need to be addressed right away, and which incidents are a secondary priority. This is one of the most frequent data lineage use cases leveraged by Vox.

Data Warehouse 52

Data Warehouse BI Data Government 52