Data Engineering Podcast

JUNE 17, 2023

Summary Architectural decisions are all based on certain constraints and a desire to optimize for different outcomes. In data systems one of the core architectural exercises is data modeling, which can have significant impacts on what is and is not possible for downstream use cases. ML, reverse ETL, etc.)

Data Lake 130

Data Lake Metadata Machine Learning Data Architecture 130

Data Engineering Podcast

SEPTEMBER 1, 2021

Summary The Presto project has become the de facto option for building scalable open source analytics in SQL for the data lake. That leaves DataOps reactive to data quality issues and can make your consumers lose confidence in your data. lets you identify data quality issues and their root causes from a single dashboard.

Data Lake 100

Data Lake Cloud AWS SQL 100

Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. Introduction to the Data Mesh Architecture and its Required Capabilities.

Architecture 124

Architecture Metadata Government Kafka 124

Databand.ai

AUGUST 30, 2023

DataOps Architecture: 5 Key Components and How to Get Started Ryan Yackel August 30, 2023 What Is DataOps Architecture? DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Monte Carlo

APRIL 1, 2021

Over the past few years, data lakes have emerged as a must-have for the modern data stack. But while the technologies powering our access and analysis of data have matured, the mechanics behind understanding this data in a distributed environment have lagged behind. Data discovery tools and platforms can help.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Rockset

APRIL 26, 2023

We’ve noticed many common patterns across streaming data architectures and we’ll be sharing a blueprint for three of the most popular: anomaly detection, IoT, and recommendations. The majority of anomaly detectors require streaming data, real-time data and historical data in order to generate inferences.

Architecture 52

Architecture Transportation Data Lake Insurance 52

Cloudera

JUNE 30, 2022

With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 86

Data Lake Business Intelligence Metadata Data Warehouse 86

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two.

Architecture 52

Architecture Data Lake Medical Datasets 52

Cloudera

NOVEMBER 17, 2022

With Cloudera Data Platform, we aim to unlock value faster and offer consistent data security and governance to meet this goal. Aqeel Ahmed Jatoi, Lead – Architecture, Governance and Control, Habib Bank Limited. Future-proof data capabilities. See other customers’ success here .

Banking 84

Banking Management Data Lake Professional Services 84

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 92

Data Lake Data Warehouse BI SQL 92

ProjectPro

JANUARY 31, 2022

This blog walks you through what does Snowflake do , the various features it offers, the Snowflake architecture, and so much more. Table of Contents Snowflake Overview and Architecture What is Snowflake Data Warehouse? Snowflake is not based on existing database systems or big data software platforms like Hadoop.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Data Engineering Podcast

SEPTEMBER 23, 2018

Using the metaphor of a museum curator carefully managing the precious resources on display and in the vaults, he discusses the various layers of an enterprise data strategy. Can you walk through the stages of an ideal lifecycle for data within the context of an organizations uses for it?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Snowflake

JANUARY 22, 2024

In 2020, Fidelity kicked off its digital transformation and established an Enterprise Data Lake (EDL) along with Data Labs. All of Fidelity’s storage abides by its data security framework and data governance policies, and provides a holistic approach to metadata management.

Engineering 63

Engineering Data Lake Unstructured Data Metadata 63

Towards Data Science

FEBRUARY 15, 2023

In this context, data management in an organization is a key point for the success of its projects involving data. One of the main aspects of correct data management is the definition of a data architecture. What is Delta Lake? The data became useless. The Lakehouse architecture was one of them.

Data Lake 77

Data Lake Data Warehouse Hadoop Data Architecture 77

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. The past decades of enterprise data platform architectures can be summarized in 69 words. Introduction to Data Mesh. The problem is not “you.”

Pharmaceutical 98

Pharmaceutical Data Lake Data Architecture Scala 98

Cloudera

MARCH 17, 2023

As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics.

Education 62

Education Unstructured Data Data Lake Data Warehouse 62

AltexSoft

FEBRUARY 11, 2023

To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. Sample of a high-level data architecture blueprint for Azure BI programs.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Cloudera

MARCH 23, 2022

In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. 1: Multi-function analytics . 3: Open Performance.

Metadata 90

Metadata Data Architecture BI Machine Learning 90

Cloudera

SEPTEMBER 15, 2022

Modern data platforms deliver an elastic, flexible, and cost-effective environment for analytic applications by leveraging a hybrid, multi-cloud architecture to support data fabric, data mesh, data lakehouse and, most recently, data observability. Luke: What is a modern data platform?

Data Lake 81

Data Lake Analytics Application Cloud Storage Architecture 81

The Modern Data Company

MARCH 1, 2024

For today’s Chief Data Officers (CDOs) and data teams, the struggle is real. We’re drowning in data yet thirsting for actionable insights. We need a new approach, a paradigm shift that delivers data with the agility and efficiency of a speedboat – enter Data Products.

Database-centric 40

Database-centric Data Lake Government Retail 40

Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Central to this transformation are two shifts. Let’s take a closer look.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Data Engineering Weekly

JANUARY 15, 2023

SiliconANGLE theCUBE: Analyst Predictions 2023 - The Future of Data Management By far one of the best analyses of trends in Data Management. 2023 predictions from the panel are; Unified metadata becomes kingmaker. The author writes a few best practices for managing medallion-style architecture.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

AltexSoft

MARCH 30, 2023

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. The relatively new storage architecture powering Databricks is called a data lakehouse. Databricks lakehouse platform architecture.

Scala 64

Scala Data Lake BI Google Cloud 64

Ascend.io

MARCH 14, 2023

Data represents our present and our future, and therein lies a significant problem: the more data you’re dealing with, the more challenging it will be to scale your company in a sustainable and standardized way. What Is a Data Mesh? It provides a more distributed, decentralized, and resilient approach to data management.

Government 52

Government Architecture Data Lake Data 52

Ascend.io

MARCH 14, 2023

Data represents our present and our future, and therein lies a significant problem: the more data you’re dealing with, the more challenging it will be to scale your company in a sustainable and standardized way. What Is a Data Mesh? It provides a more distributed, decentralized, and resilient approach to data management.

Government 52

Government Architecture Data Lake Data 52

AltexSoft

MAY 12, 2023

Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. There are several widely used unstructured data storage solutions such as data lakes (e.g., Build data architecture.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Silectis

JANUARY 3, 2021

Big Query Google’s cloud data warehouse. Data Architecture Data architecture is a composition of models, rules, and standards for all data systems and interactions between them. Data Catalog An organized inventory of data assets relying on metadata to help with data management.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Monte Carlo

JULY 30, 2020

In the age of self-service business intelligence , nearly every company considers themselves a data-first company, but not every company is treating their data architecture with the level of democratization and scalability it deserves. Your company, for one, views data as a driver of innovation. What is a data mesh?

IT 45

IT Data Lake Business Intelligence Data Architecture 45

AltexSoft

OCTOBER 30, 2021

Such visualizations as graphs and charts are typically prepared by data analysts or business analysts, though not every project has those people employed. Then, a data scientist uses complex business intelligence tools to present business insights to executives. Data engineer’s responsibilities — Development and Architecture.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Figure 2: Example data pipeline with DataOps automation. In this project, I automated data extraction from SFTP, the public websites, and the email attachments. Monitoring Job Metadata.

Engineering 60

Engineering BI Business Analyst Metadata 60

Towards Data Science

APRIL 3, 2023

Zero-ETL changes this ingestion process by having the transactional database do the data cleaning and normalization prior to automatically loading it into the data warehouse. It’s important to note the data is still in a relatively raw state. No duplicate data storage. Pros : Reduced latency. One less source for failure.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

Advancing Analytics: Data Engineering

NOVEMBER 10, 2020

We have discussed in the past this idea of the lakehouse , the aspirational target of many analytics platforms these days of combining the huge power and potential of data lakes with the rigour, reliability and concurrency of a data warehouse. The Lakehouse Architecture. Get In Touch. Simon Whiteley.

SQL 52

SQL BI Data Warehouse Data Lake 52

Knowledge Hut

SEPTEMBER 29, 2023

By combining data from various structured and unstructured data systems into structures, Microsoft Azure Data Engineers will be able to create analytics solutions. Why Should You Get an Azure Data Engineer Certification? You can browse the data lake files with the interactive training material.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Cloudera

AUGUST 21, 2020

Data-in-motion is predominantly about streaming data so enterprises typically have two different ways or binary ways of looking at data. The governance aspect is perhaps even more important and businesses need to be able to understand where the data comes from.

Banking 61

Banking Kafka Cloud Storage Government 61