Data Engineering Podcast

DECEMBER 3, 2023

Summary The first step of data pipelines is to move the data to a place where you can process and prepare it for its eventual purpose. Data transfer systems are a critical component of data enablement, and building them to support large volumes of information is a complex endeavor.

Systems 130

Systems Designing Data Lake SQL 130

Data Engineering Podcast

JULY 17, 2022

Whether that data is public, paid, or scraped it requires investment and upkeep to acquire and integrate it with your systems. What are the categories of information that organizations use external data sources for? What are the steps to on-board new data sources? Can you describe what Crux is and the story behind it?

Data Management 130

Data Management Management Metadata MongoDB 130

Picnic Engineering

OCTOBER 17, 2023

As organizations seek to gain value out of data, AI models garner the spotlight, and a building block to unlock their potential is strong Master Data Management (MDM). The truth is, as companies want to unlock the power of data this starts with strong MDM. Generally MDM doesn’t receive the public attention it deserves.

Data Management 52

Data Management Management Food Data 52

Precisely

SEPTEMBER 5, 2023

With cloud computing, the capacity to extract value from data is greater than ever. As this realization grows, businesses are shifting their investments from hardware to technologies that optimize data assets. Master Data Management systems (MDM) play an important role in harmonizing data assets across large and midsize enterprises.

Data Governance 52

Data Governance Government Data Management Management 52

Pinterest Engineering

OCTOBER 2, 2024

As a data serving platform, SDS is responsible for various aspects of the data lifecycle management, including: Online Query Serving , which offers multiple data models such as graph, table, document, etc. Sparrow, our transactional management system that exposes a similar interface to HBase.

Data Management 56

Data Management Management Metadata SQL 56

LinkedIn Engineering

JULY 19, 2023

End-users create relational entities in the form of Tables over structured or semi-structured data using compute engines, with the metadata for a Table stored in a catalog, and data stored in distributed storage. While functional, our current setup for managing tables is fragmented. retention, replication), optimal (e.g.,

Big Data 78

Big Data Data Management Management Metadata 78

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Data Engineering Podcast

MAY 12, 2024

Summary Building a data platform is a substrantial engineering endeavor. Once it is running, the next challenge is figuring out how to address release management for all of the different component parts. The services and systems need to be kept up to date, but so does the code that controls their behavior.

Management 147

Management Data Lake High Quality Data Machine Learning 147

Data Engineering Podcast

NOVEMBER 16, 2020

In this episode CEO and co-founder of Isima Darshan Rawal explains how the biOS platform is architected to enable ease of use, the challenges that were involved in building an entirely new system from scratch, and how it can integrate with the rest of your data platform to allow for incremental adoption.

Data Management 100

Data Management Management BI Business Intelligence 100

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing.

Data Management 52

Data Management Management Data Lake Data Governance 52

U-Next

SEPTEMBER 7, 2022

Employee database software is quickly becoming a must-have for HR and people managers. Companies can achieve new heights with the right management and administration tools. A firm can benefit immensely from maintaining accurate and clean employee data, as it is still a difficult task. . What Is Employee Data Management? .

Data Management 52

Data Management Management Electronics Unstructured Data 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing.

Data Management 52

Data Management Management Data Lake Data Governance 52

Data Engineering Podcast

JULY 5, 2021

Summary At the core of every data pipeline is an workflow manager (or several). Deploying, managing, and scaling that orchestration can consume a large fraction of a data team’s energy so it is important to pick something that provides the power and flexibility that you need.

Systems 100

Systems Management Data Warehouse Programming Language 100

RandomTrees

NOVEMBER 5, 2024

Good data management in Salesforce provides insight into improving interactions with customers and making business operations easier. In this blog, we will take you through the basic steps that help in managing data effectively in Salesforce. Step 1: Understand Your Data Model 1.1 Step 3: Data Integration 3.1.

Management 52

Management Data Utilities Data Validation 52

phData: Data Engineering

NOVEMBER 8, 2024

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Open Table Format (OTF) architecture now provides a solution for efficient data storage, management, and processing while ensuring compatibility across different platforms.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Ascend.io

AUGUST 15, 2023

This same principle holds true in data management. It’s no surprise, then, that the quest for Fivetran alternatives is on the rise as organizations set their sights on a more holistic data approach. Defense: Saving Money with Intelligent Data Refresh In football, a solid defense does more than just stop goals.

Data Management 52

Data Management Management Data Ingestion Data Pipeline 52

Data Engineering Podcast

NOVEMBER 20, 2022

In this episode Ian Schweer shares his experiences at Riot Games supporting player-focused features such as machine learning models and recommeder systems that are deployed as part of the game binary. The biggest challenge with modern data systems is understanding what data you have, where it is located, and who is using it.

Systems 130

Systems Metadata Data Pipeline MongoDB 130

Data Engineering Weekly

SEPTEMBER 26, 2024

Privacy and access management within data infrastructure is not just a best practice; it's a necessity. Regulations like GDPR (General Data Protection Regulation), focusing on data subject rights and cross-border data flows, have significant implications for data handling practices. Why care about privacy?

Systems 67

Systems Engineering Data Warehouse Architecture 67

Data Engineering Podcast

SEPTEMBER 3, 2018

Summary With the proliferation of data sources to give a more comprehensive view of the information critical to your business it is even more important to have a canonical view of the entities that you care about. Can you start by establishing a definition of data mastering that we can work from?

Data Management 100

Data Management Management Relational Database Business Intelligence 100

Data Engineering Podcast

DECEMBER 25, 2022

Recognizing this shortcoming and the capabilities that could be unlocked by a robust solution Rishabh Poddar helped to create Opaque Systems as an outgrowth of his PhD studies. Can you describe what you are building at Opaque Systems and the story behind it? When is Opaque the wrong choice?

Machine Learning 130

Machine Learning Systems Data Lake Data Warehouse 130

Cloudera

DECEMBER 16, 2022

We are pleased to announce that Cloudera has been named a Leader in the 2022 Gartner ® Magic Quadrant for Cloud Database Management Systems. We’re proud to be recognized for the data management and data analytics innovations we have delivered in the new Cloudera Data Platform (CDP).

Database 90

Database Cloud Systems Management 90

Data Engineering Podcast

FEBRUARY 20, 2022

Summary The life sciences as an industry has seen incredible growth in scale and sophistication, along with the advances in data technology that make it possible to analyze massive amounts of genomic information. Interview Introduction (see Guy’s bio below) How did you get involved in the area of data management?

Systems 100

Systems Software Engineer Software Engineering Data Warehouse 100

Knowledge Hut

DECEMBER 28, 2023

The information system is a very vast concept that encompasses several aspects like database management, the communication system, various devices, several connections, the internet, collection, organization, and storing data and other information-related applications that are typically used in a business forum.

Systems 52

Systems Telecommunication Technology Certification 52

Precisely

JUNE 19, 2024

As consumer expectations for efficient and personalized experiences continue to rise, effectively managing customer relationships and communications is more crucial than ever. What is CRM (Customer Relationship Management)? Marketing automation: Manage marketing campaign tasks, including email marketing and social media interactions.

Management 59

Management Media Government Systems 59

Towards Data Science

FEBRUARY 6, 2024

ERP and CRM systems are designed and built to fulfil a broad range of business processes and functions. This generalisation makes their data models complex and cryptic and require domain expertise. As you do not want to start your development with uncertainty, you decide to go for the operational raw data directly.

Systems 78

Systems Raw Data Metadata Data Cleanse 78

ProjectPro

FEBRUARY 16, 2023

With so much riding on the efficiency of ETL processes for data engineering teams, it is essential to take a deep dive into the complex world of ETL on AWS to take your data management to the next level. AWS refers to Amazon Web Service, the most widely used cloud computing system.

AWS 52

AWS Data Management ETL Tools Management 52

InData Labs

DECEMBER 9, 2021

In today’s digitized medical landscape, effective treatment and better outcomes for patients depend on the smart use of medical data. Healthcare data management treats data as a powerful asset and improves health services. The rise of EHR/EMR systems also promotes more effective handling of patient data.

Healthcare 52

Healthcare Data Management Medical IT 52

Data Engineering Podcast

JULY 6, 2020

Summary There are an increasing number of use cases for real time data, and the systems to power them are becoming more mature. Once you have a streaming platform up and running you need a way to keep an eye on it, including observability, discovery, and governance of your data. That’s what the Lenses.io

Systems 100

Systems Kafka SQL Data Engineer 100

Cloudera

FEBRUARY 4, 2021

Financial services institutions need the ability to analyze and act on massive volumes of data from diverse sources in order to monitor, model, and manage risk across the enterprise. They need a comprehensive data and analytics platform to model risk exposures on-demand. End-to-end Data Lifecycle.

Technology 86

Technology Data Management Management Insurance 86

Data Engineering Podcast

FEBRUARY 1, 2021

It is eminently possible to generate millions or billions of data points per second, the information needs to be propagated to a central location, processed, and analyzed in timeframes on the order of milliseconds or single-digit seconds, and the consumers of the data need to be able to query the information quickly and flexibly.

Systems 100

Systems Cloud BI Data Warehouse 100

Data Engineering Podcast

APRIL 24, 2022

WhyLogs is a powerful library for flexibly instrumenting all of your data systems to understand the entire lifecycle of your data from source to productionized model. You have full control over your data and their plugin system lets you integrate with all of your other data tools, including data warehouses and SaaS platforms.

Machine Learning 100

Machine Learning Systems Data Lake Java 100

Data Engineering Podcast

DECEMBER 19, 2021

Summary Building a well managed data ecosystem for your organization requires a holistic view of all of the producers, consumers, and processors of information. The team at Metaphor are building a fully connected metadata layer to provide both technical and social intelligence about your data. No more scripts, just SQL.

Systems 100

Systems Building Metadata Data Warehouse 100

Data Engineering Podcast

SEPTEMBER 11, 2022

Summary Data engineering systems are complex and interconnected with myriad and often opaque chains of dependencies. As they scale, the problems of visibility and dependency management can increase at an exponential rate. Interview Introduction How did you get involved in the area of data management?

Systems 100

Systems Metadata Building MongoDB 100

The Modern Data Company

APRIL 7, 2023

It is important to note that data debt has methodological and technological components. Data management technologies grow old and out of date. The longer an organization ignores its data debt, the worse it will become. Poor data quality – Poor data handling inevitably leads to inaccuracies within it.

Management 98

Management Government Data Data Management 98