Hevo

JUNE 7, 2024

A schema is a logical representation of how data is organized into tables. Before importing any dataset into a data warehouse platform like Snowflake, it is necessary to understand how to create a schema in Snowflake. This allows better organization and accessibility of your data in the Snowflake environment.

Data Management 40

Data Management Management Data Warehouse Datasets 40

Data Engineering Podcast

JANUARY 18, 2021

Summary The data warehouse has become the central component of the modern data stack. This is an interesting conversation about the importance of the data warehouse and how it can be used beyond just internal analytics. And don’t forget to thank them for their continued support of this show!

Data Warehouse 100

Data Warehouse BI Data Data Pipeline 100

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Data Engineering Podcast

JULY 17, 2022

Summary There are extensive and valuable data sets that are available outside the bounds of your organization. Whether that data is public, paid, or scraped it requires investment and upkeep to acquire and integrate it with your systems. Atlan is the metadata hub for your data ecosystem.

Data Management 130

Data Management Management Metadata MongoDB 130

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 Data Lake Management 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 Data Lake Management 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 Data Lake Management Data Warehouse 52

Picnic Engineering

OCTOBER 17, 2023

Building the data foundation for world’s best online supermarket The Importance of MDM In the fast-paced world of technology, it’s easy to be captivated by the allure of artificial intelligence. The truth is, as companies want to unlock the power of data this starts with strong MDM. Picnic’s MDM Journey Picnic was founded in 2015.

Data Management 52

Data Management Management Food 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

NOVEMBER 26, 2019

As they scaled the volume of customers and data they began running into the limitations of their initial architecture. With 200Gbit private networking, scalable shared block storage, and a 40Gbit public network, you’ve got everything you need to run a fast, reliable, and bullet-proof data platform.

Data Warehouse 100

Data Warehouse Building PostgreSQL Kafka 100

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

Data Science Blog: Data Engineering

MAY 20, 2024

Continuous Integration and Continuous Delivery (CI/CD) for Data Pipelines: It is a Game-Changer with AnalyticsCreator! The need for efficient and reliable data pipelines is paramount in data science and data engineering. CI/CD for Data Pipelines Data pipelines provide consistency, reduce errors, and increase efficiency.

Data Pipeline 52

Data Pipeline BI Data Lake Data Warehouse 52

Data Engineering Podcast

FEBRUARY 19, 2023

Summary Cloud data warehouses have unlocked a massive amount of innovation and investment in data applications, but they are still inherently limiting. Because of their complete ownership of your data they constrain the possibilities of what data you can store and how it can be used. We feel your pain.

IT 147

IT Data Lake Metadata Data Warehouse 147

Cloudera

SEPTEMBER 10, 2018

Among the many reasons that a majority of large enterprises have adopted Cloudera Data Warehouse as their modern analytic platform of choice is the incredible ecosystem of partners that have emerged over recent years. Informatica’s Big Data Manager and Qlik’s acquisition of Podium Data are just 2 examples.

Data Warehouse 43

Data Warehouse BI Unstructured Data Data 43

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. 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

SEPTEMBER 3, 2023

Summary Cloud data warehouses and the introduction of the ELT paradigm has led to the creation of multiple options for flexible data integration, with a roughly equal distribution of commercial and open source options. It’s the only true SQL streaming database built from the ground up to meet the needs of modern data products.

Data Integration 162

Data Integration BI SQL Python 162

Snowflake

NOVEMBER 30, 2023

At TCS , we help companies shift their enterprise data warehouse (EDW) platforms to the cloud as well as offering IT services. We’re extremely familiar with just how tricky a cloud migration can be, especially when it involves moving historical business data. How many tables and views will be migrated, and how much raw data?

Data Warehouse 100

Data Warehouse Banking Data Cloud 100

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

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 Data Lake 130

Data Engineering Podcast

MAY 29, 2022

Summary The latest generation of data warehouse platforms have brought unprecedented operational simplicity and effectively infinite scale. In order to ensure that you can explore and analyze your data without spending money on inefficient queries Mingsheng Hong and Zheng Shao created Bluesky Data.

Cloud 100

Cloud Data Warehouse Data Lake Data 100

Knowledge Hut

APRIL 25, 2024

Big data in information technology is used to improve operations, provide better customer service, develop customized marketing campaigns, and take other actions to increase revenue and profits. It is especially true in the world of big data. It is especially true in the world of big data. What Are Big Data T echnologies?

Big Data 98

Big Data Technology NoSQL Hadoop 98

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

Cloudera

MAY 30, 2024

The financial services industry is undergoing a significant transformation, driven by the need for data-driven insights, digital transformation, and compliance with evolving regulations. What are some of the reasons that TAI Solutions’ customers choose Cloudera?

Data Analytics 81

Data Analytics Banking Insurance Finance 81

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

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

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 9, 2020

Summary Designing the structure for your data warehouse is a complex and challenging process. As businesses deal with a growing number of sources and types of information that they need to integrate, they need a data modeling strategy that provides them with flexibility and speed.

Data Lake 100

Data Lake Data Warehouse Hadoop NoSQL 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. Missing data?

Systems 100

Systems Building Metadata Data Warehouse 100

Knowledge Hut

MARCH 7, 2024

The year 2024 saw some enthralling changes in volume and variety of data across businesses worldwide. The surge in data generation is only going to continue. Foresighted enterprises are the ones who will be able to leverage this data for maximum profitability through data processing and handling techniques.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

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

Christophe Blefari

JUNE 16, 2023

I'm now under the Berlin rain with 20° When I write in these conditions I feel like a tortured author writing a depressing novel while actually today I'll speak about the AI Act, Python, SQL and data platforms. Mainly he unit tests macros (the logic) with his framework and test data with soda and dbt contracts.

Programming Language 130

Programming Language SQL PostgreSQL Data 130

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

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

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 Hadoop SQL 100

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

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

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 82

Data Warehouse Database-centric Metadata Cloud 82