Monte Carlo

FEBRUARY 6, 2023

So, you’re planning a cloud data warehouse migration. But be warned, a warehouse migration isn’t for the faint of heart. As you probably already know if you’re reading this, a data warehouse migration is the process of moving data from one warehouse to another. A worthy quest to be sure.

Data Warehouse 52

Data Warehouse AWS Data Validation Data 52

Data Engineering Weekly

MAY 26, 2024

link] Meta: Composable data management at Meta Meta writes about its transition to a composable data management system to improve interoperability, reusability, and engineering efficiency. seconds, enhancing real-time sports data analytics efficiency! The author highlights some of the key missing features from S3.

Data Engineering 76

Data Engineering Data Engineer Engineering Google Cloud 76

Data Engineering Podcast

DECEMBER 16, 2018

Summary Every business needs a pipeline for their critical data, even if it is just pasting into a spreadsheet. As the organization grows and gains more customers, the requirements for that pipeline will change. Can you start by sharing your definition of a data pipeline? What are your thoughts on that approach?

Data Pipeline 100

Data Pipeline Data Lake Data Warehouse Python 100

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. As data is expanding exponentially, organizations struggle to harness digital information's power for different business use cases.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

FEBRUARY 16, 2023

ETL is a critical component of success for most data engineering teams, and with teams harnessing it with the power of AWS, the stakes are higher than ever. Data Engineers and Data Scientists require efficient methods for managing large databases, which is why centralized data warehouses are in high demand.

AWS 52

AWS Data Management ETL Tools Management 52

Ascend.io

APRIL 12, 2023

Right now, at this moment, are you prepared to act on your company’s data? So when we talk about making data usable, we’re having a conversation about data integrity. Data integrity is the overall readiness to make confident business decisions with trustworthy data, repeatedly and consistently. If not, why?

Data Pipeline 52

Data Pipeline Data Integration Datasets Data 52

Data Engineering Podcast

DECEMBER 4, 2022

Summary The term "real-time data" brings with it a combination of excitement, uncertainty, and skepticism. In this episode Arjun Narayan explains how the technical barriers to adopting real-time data in your analytics and applications have become surmountable by organizations of all sizes.

Data Lake 100

Data Lake MongoDB MySQL Data Warehouse 100

Data Engineering Podcast

NOVEMBER 6, 2022

Summary Despite the best efforts of data engineers, data is as messy as the real world. Entity resolution and fuzzy matching are powerful utilities for cleaning up data from disconnected sources, but it has typically required custom development and training machine learning models.

MongoDB 130

MongoDB Scala MySQL Machine Learning 130

Data Engineering Podcast

AUGUST 3, 2021

Summary Data lake architectures have largely been biased toward batch processing workflows due to the volume of data that they are designed for. With more real-time requirements and the increasing use of streaming data there has been a struggle to merge fast, incremental updates with large, historical analysis.

Data Lake 130

Data Lake Data Warehouse Hadoop Architecture 130

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. RudderStack’s smart customer data pipeline is warehouse-first. How does it work?

Systems 100

Systems Software Engineer Software Engineering Data Warehouse 100

Knowledge Hut

MARCH 28, 2024

Data science has become one of the most trending fields today. Data engineering is one of them. According to AnalytixLabs , the data science market is expected to be worth USD 230.80 This demonstrates the increasing need for Microsoft Certified Data Engineers. That’s where data engineers are on the go.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Data Engineering Podcast

MARCH 29, 2021

Summary Data quality is on the top of everyone’s mind recently, but getting it right is as challenging as ever. In this episode Maarten Masschelein and Tom Baeyens share the work they are doing at Soda to bring everyone on board to make your data clean and reliable.

Management 100

Management Data Warehouse BI Data Pipeline 100

Data Engineering Podcast

DECEMBER 4, 2022

Summary Business intelligence is the foremost application of data in organizations of all sizes. Zing Data is building a mobile native platform for business intelligence. Atlan is the metadata hub for your data ecosystem. Data engineers don’t enjoy writing, maintaining, and modifying ETL pipelines all day, every day.

Business Intelligence 100

Business Intelligence Metadata BI MongoDB 100

Data Engineering Podcast

APRIL 26, 2021

Summary The reason for collecting, cleaning, and organizing data is to make it usable by the organization. In this episode Maxime Beauchemin discusses how data engineers can use Superset to provide self service access to data and deliver analytics. Give it a listen and then take it for a test drive today.

Business Intelligence 100

Business Intelligence Data Warehouse Hadoop Data Pipeline 100

Data Engineering Podcast

DECEMBER 4, 2021

Summary Hiring data professionals is challenging for a multitude of reasons, and as with every interview process there is a potential for bias to creep in. The whole process of hiring is an important organizational skill to cultivate and this is an interesting exploration of the specific challenges involved in finding data professionals.

Data Warehouse 100

Data Warehouse Data Lake BI Business Intelligence 100

Data Engineering Podcast

JANUARY 7, 2022

Summary Data observability is a set of technical and organizational capabilities related to understanding how your data is being processed and used so that you can proactively identify and fix errors in your workflows. Today’s episode is Sponsored by Prophecy.io – the low-code data engineering platform for the cloud.

BI 100

BI Data Warehouse Metadata SQL 100

Data Engineering Podcast

FEBRUARY 22, 2021

Summary Data integration is a critical piece of every data pipeline, yet it is still far from being a solved problem. There are a number of managed platforms available, but the list of options for an open source system that supports a large variety of sources and destinations is still embarrasingly short.

Data Integration 100

Data Integration Data Warehouse Data Pipeline BI 100

Data Engineering Podcast

JULY 3, 2022

Summary The ecosystem for data tools has been going through rapid and constant evolution over the past several years. These technological shifts have brought about corresponding changes in data and platform architectures for managing data and analytical workflows. Atlan is the metadata hub for your data ecosystem.

Architecture 100

Architecture Metadata MongoDB MySQL 100

Data Engineering Podcast

JULY 19, 2021

Summary Data quality is a concern that has been gaining attention alongside the rising importance of analytics for business success. While those are useful tools, it is far better to prevent data errors before they become an outsized issue. RudderStack’s smart customer data pipeline is warehouse-first.

Management 100

Management Data Warehouse Data Pipeline Data 100

Data Engineering Podcast

FEBRUARY 15, 2021

Summary Every business aims to be data driven, but not all of them succeed in that effort. In order to be able to truly derive insights from the data that an organization collects, there are certain foundational capabilities that they need to have capacity for.

Building 100

Building Data Warehouse BI Data Pipeline 100

Data Engineering Podcast

NOVEMBER 4, 2021

Summary The precursor to widespread adoption of cloud data warehouses was the creation of customer data platforms. Acting as a centralized repository of information about how your customers interact with your organization they drove a wave of analytics about how to improve products based on actual usage data.

Data Warehouse 100

Data Warehouse Business Intelligence ETL System Data Lake 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. Struggling with broken pipelines?

Systems 100

Systems Building Metadata Data Warehouse 100

Data Engineering Podcast

DECEMBER 11, 2022

Summary One of the most critical aspects of software projects is managing its data. Managing the operational concerns for your database can be complex and expensive, especially if you need to scale to large volumes of data, high traffic, or geographically distributed usage.

Database 100

Database MySQL Data Lake MongoDB 100

Data Engineering Podcast

OCTOBER 22, 2021

In this episode Oliver Laslett describes why dashboards aren’t sufficient for business analytics, how Lightdash promotes the work that you are already doing in your data warehouse modeling with dbt, and how they are focusing on bridging the divide between data teams and business teams and the requirements that they have for data workflows.

Engineering 100

Engineering Business Intelligence BI Data Warehouse 100

Data Engineering Podcast

JANUARY 1, 2022

Summary This has been an active year for the data ecosystem, with a number of new product categories and substantial growth in existing areas. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. Missing data?

Data Warehouse 100

Data Warehouse Data Lake SQL Hadoop 100

Data Engineering Podcast

JUNE 19, 2022

Summary Data analysis is a valuable exercise that is often out of reach of non-technical users as a result of the complexity of data systems. Atlan is the metadata hub for your data ecosystem. Modern data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Metadata 130

Metadata Unstructured Data MongoDB MySQL 130

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

Data Engineering Podcast

JULY 10, 2022

Summary Building a data platform is a journey, not a destination. In this episode Inbar Yogev and Lior Winner share the journey that they and their teams at Riskified have been on for their data platform. They also discuss how they have established a guild system for training and supporting data professionals in the organization.

Metadata 100

Metadata MongoDB MySQL Data Pipeline 100

Data Engineering Podcast

APRIL 5, 2021

Summary One of the biggest obstacles to success in delivering data products is cross-team collaboration. This introduces a barrier to communication that is difficult to overcome, particularly in teams that have not reached a significant level of maturity in their data journey.

Data Warehouse 100

Data Warehouse Data Pipeline BI Metadata 100

Data Engineering Podcast

AUGUST 10, 2021

Summary All of the fancy data platform tools and shiny dashboards that you use are pointless if the consumers of your analysis don’t have trust in the answers. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform.

IT 130

IT Building Data Warehouse Python 130

Data Engineering Podcast

MARCH 22, 2021

For analytical systems, the only way to provide this reliably is by implementing change data capture (CDC). Unfortunately, this is a non-trivial undertaking, particularly for teams that don’t have extensive experience working with streaming data and complex distributed systems.

Data Warehouse 100

Data Warehouse Metadata Data Lake Hadoop 100

Towards Data Science

FEBRUARY 6, 2024

This generalisation makes their data models complex and cryptic and require domain expertise. Even harder to manage, a common setup within large organisations is to have several instances of these systems with some underlaying processes in charge of transmitting data among them, which could lead to duplications, inconsistencies, and opacity.

Systems 81

Systems Raw Data Metadata Data Cleanse 81

Data Engineering Podcast

APRIL 12, 2021

Summary "Business as usual" is changing, with more companies investing in data as a first class concern. As a result, the data team is growing and introducing more specialized roles. If you are wondering how to apply your talents and interests to working with data then this episode is a must listen.

Data Warehouse 100

Data Warehouse Data Pipeline BI Data 100

Data Engineering Podcast

MARCH 8, 2021

Summary A majority of the time spent in data engineering is copying data between systems to make the information available for different purposes. This introduces challenges such as keeping information synchronized, managing schema evolution, building transformations to match the expectations of the destination systems.

IT 100

IT Data Warehouse MongoDB Kafka 100

Data Engineering Podcast

OCTOBER 9, 2022

Summary The core of any data platform is the centralized storage and processing layer. For many that is a data warehouse, but in order to support a diverse and constantly changing set of uses and technologies the data lakehouse is a paradigm that offers a useful balance of scale and cost, with performance and ease of use.

Metadata 100

Metadata AWS MongoDB MySQL 100

Data Engineering Podcast

DECEMBER 11, 2021

In order to make it easier for developers to build customer profiles in a way that respects their privacy Serge Huber helped to create the Apache Unomi framework as an open source customer data platform. Struggling with broken pipelines? Missing data? Start trusting your data with Monte Carlo today! Stale dashboards?

Data Warehouse 100

Data Warehouse Raw Data Data Lake BI 100

Data Engineering Podcast

JUNE 5, 2022

Summary The best way to make sure that you don’t leak sensitive data is to never have it in the first place. The team at Skyflow decided that the second best way is to build a storage system dedicated to securely managing your sensitive information and making it easy to integrate with your applications and data systems.

Data Security 100

Data Security Metadata MongoDB Scala 100