Data Engineering Podcast

JULY 3, 2022

Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value. Tired of deploying bad data?

Architecture 100

Architecture Metadata MongoDB MySQL 100

Monte Carlo

AUGUST 31, 2023

Data is a priority for your CEO, as it often is for digital-first companies, and she is fluent in the latest and greatest business intelligence tools. What about a frantic email from your CTO about “duplicate data” in a business intelligence dashboard?

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

DECEMBER 21, 2023

In this article, we will understand the promising data engineer career outlook and what it takes to succeed in this role. What is Data Engineering? Data engineering is the method to collect, process, validate and store data. It involves building and maintaining data pipelines, databases, and data warehouses.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineering is typically a software engineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. Let us first get a clear understanding of why Data Science is important. What is the need for Data Science?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

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 product includes data and operations.

Pharmaceutical 98

Pharmaceutical Data Lake Data Architecture Scala 98

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. machine learning and deep learning models; and business intelligence tools.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Monte Carlo

JANUARY 23, 2023

In this post we compare and contrast the data mesh vs data lake to illustrate the benefits of each and help discover what’s right for your data platform. In a self-service data landscape, every team wants their business intelligence served up hot and fast. Image courtesy of Monte Carlo Data.)

Data Lake 52

Data Lake Unstructured Data Business Intelligence Architecture 52

Precisely

MARCH 14, 2023

And the desire to leverage those technologies for analytics, machine learning, or business intelligence (BI) has grown exponentially as well. We optimize these products for use cases and architectures that will remain business-critical for years to come. What does all this mean for your business?

Data Integration 52

Data Integration High Quality Data BI Data 52

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. This unchanging schema forms the foundation for all queries and business intelligence.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Silectis

JANUARY 3, 2021

If you’re new to data engineering or are a practitioner of a related field, such as data science, or business intelligence, we thought it might be helpful to have a handy list of commonly used terms available for you to get up to speed. Big Data Large volumes of structured or unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

The Modern Data Company

JANUARY 31, 2023

This post highlights exactly how our founders taught us to think differently about data and why it matters. Here are the cornerstones of this new paradigm: Data ownership is a construct Data pipelines should be accessible to everyone Data products should adapt to the organization, not vice versa.

Retail 98

Retail Healthcare Data Architecture Data Pipeline 98

Knowledge Hut

MAY 3, 2024

A new breed of ‘Fast Data’ architectures has evolved to be stream-oriented, where data is processed as it arrives, providing businesses with a competitive advantage. Dean Wampler (Renowned author of many big data technology-related books) Dean Wampler makes an important point in one of his webinars.

Kafka 98

Kafka Scala Java Amazon Web Services 98

AltexSoft

OCTOBER 30, 2021

They’re integral specialists in data science projects and cooperate with data scientists by backing up their algorithms with solid data pipelines. Juxtaposing data scientist vs engineer tasks. One data scientist usually needs two or three data engineers. Providing data access tools.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

Knowledge Hut

JUNE 30, 2023

The essential theories, procedures, and equipment for creating trustworthy and effective data systems are covered in this book. It explores subjects including data modeling, data pipelines, data integration, and data quality, offering helpful advice on organizing and implementing reliable data solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 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? Traditional data warehouse platform architecture. Data lake architecture example.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Monte Carlo

JULY 30, 2020

But what is a data mesh and why should you build one? 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.

IT 45

IT Data Lake Business Intelligence Data Architecture 45

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. They are responsible for changing the design, development, and management of data pipelines while also managing the data sources for effective data collection.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

AltexSoft

MARCH 30, 2023

What Databricks is used for Use cases for Databricks are as diverse and numerous as the types of data and the range of tools and operations it supports. Watch our video to learn more about one of the key Databricks applications — data engineering. Databricks focuses on data engineering and data science.

Scala 64

Scala Data Lake BI Google Cloud 64

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. Priyanjna Sharma.

Engineering 60

Engineering BI Business Analyst Metadata 60

Edureka

FEBRUARY 9, 2023

This includes practical knowledge of data ingestion methods like incremental loading and bulk loading, as well as experience with data transformation using Azure Data Factory. It’s a versatile language that is well-suited to a wide range of data engineering tasks, and its use in Azure is widespread.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Monte Carlo

MARCH 28, 2024

For the past few decades, most companies have kept data in an organizational silo. Analytics teams served business units, and even as data became more crucial to decision-making and product roadmaps, the teams in charge of data pipelines were treated more like plumbers and less like partners.

Data 52

Data High Quality Data Machine Learning Accessible 52

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Rockset

JANUARY 3, 2023

For people creating this data, understanding these new concepts and principles requires data to be treated like a product so that other people can consume it easily with fewer barriers of access. The cloud is the great efficiency enabler of real-time streaming data stacks With streaming data, the data never stops coming.

Data Warehouse 52

Data Warehouse Education Database Data 52

Databand.ai

DECEMBER 20, 2022

Neelesh regularly shares his advice channels, including as a recent guest on Databand’s MAD Data Podcast , where he spoke about how engineering can deliver better value for data science. On LinkedIn, he posts frequently about data engineering, data architecture, interview preparation, and career advice.

Data Analytics 52

Data Analytics Google Cloud Data Science Data Mining 52

Knowledge Hut

SEPTEMBER 26, 2023

This integration simplifies data access and management within the Azure cloud environment. Third-Party Integrations: Databricks offers connectors and integrations with popular third-party tools and services, including business intelligence (BI) platforms, data visualization tools, and machine learning frameworks.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Advancing Analytics: Data Engineering

NOVEMBER 10, 2020

Data Engineers – Whereas the ETL developer of the past was largely an extension of BI departments, modern data engineers are more technically adept, bringing an understanding of software engineering to the development of robust, performant data pipelines.

SQL 52

SQL BI Data Warehouse Data Lake 52

Monte Carlo

MAY 17, 2023

Data Warehouse (Or Lakehouse) Migration 34. Integrate Data Stacks Post Merger 35. Know When To Fix Vs. Refactor Data Pipelines Improve DataOps Processes 37. Analyze Data Incident Impact and Triage 39. Transition To A Data Mesh (Or Other Data Team Structure) 40. Prioritize Data Assets And Efforts 41.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Data warehouse (or Lakehouse) migration 34. Integrate Data Stacks Post Merger 35. Know When To Fix Vs. Refactor Data Pipelines Improve DataOps Processes 37. Analyze Data Incident Impact and Triage 39. Transition To A Data Mesh (Or Other Data Team Structure) 40. Prioritize Data Assets And Efforts 41.

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52

Databand.ai

DECEMBER 13, 2022

We’d be remiss not to share that Joseph was a recent guest on Databand’s MAD Data Podcast , where he discussed ways to keep data systems from becoming unwieldy and shared tips for data teams to manage their data warehouses and keep data pipelines running reliably. You can also watch the video recording.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Monte Carlo

AUGUST 17, 2021

Data informs every business decision, from customer support to feature development, and most recently, how to support pricing plans for organizations most affected during COVID-19. When migrating to Snowflake, PagerDuty wanted to understand the health of their data pipelines through fully automated data observability.

Insurance 40

Insurance Retail Data Pipeline Portfolio 40

ProjectPro

JANUARY 31, 2022

This is the reason why we need Data Warehouses. What is Snowflake Data Warehouse? A Data Warehouse is a central information repository that enables Data Analytics and Business Intelligence (BI) activities. The query processing layer is separated from the disk storage layer in the Snowflake data architecture.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

phData: Data Engineering

JULY 18, 2023

CDWs are designed for running large and complex queries across vast amounts of data, making them ideal for centralizing an organization’s analytical data for the purpose of business intelligence and data analytics applications. It should also enable easy sharing of insights across the organization.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Snowflake

FEBRUARY 13, 2023

Context Analytics Context Analytics, formerly known as Social Market Analytics, has expanded its depth of data to include all textual data. The company sources, cleans, structures, and analyzes textual data for investable insights and business intelligence. customers to make informed credit decisions.

Insurance 52

Insurance Banking Government Retail 52

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

Monte Carlo

JULY 7, 2022

(Interestingly these three organizations share a need for near real-time data and have services that produce copious first-party event/transactional data). There is a communication chasm between service implementers, data engineers, and data consumers. Why are data contracts important? Or is it a passing fad?

Data Warehouse 52

Data Warehouse Software Engineer Software Engineering Data 52

ProjectPro

JUNE 9, 2021

Engineering' relates to building and designing pipelines that help acquire, process, and transform the collected data into a usable form. Data Engineering involves designing and building data pipelines that extract, analyze, and convert data into a valuable and meaningful format for predictive and prescriptive modeling.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

AltexSoft

JULY 18, 2023

Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general.

Big Data 52

Big Data Data Process Process Hadoop 52