Data Engineering Podcast

SEPTEMBER 4, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. A data observability platform?

IT 100

IT Metadata MongoDB MySQL 100

Data Engineering Podcast

JULY 3, 2022

She also discusses her views on the role of the data lakehouse as a building block for these architectures and the ongoing influence that it will have as the technology matures. Atlan is the metadata hub for your data ecosystem. Visit dataengineeringpodcast.com/datafold today to book a demo with Datafold.

Architecture 100

Architecture Metadata MongoDB MySQL 100

Data Engineering Podcast

JUNE 5, 2022

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. Atlan is the metadata hub for your data ecosystem. Data teams are increasingly under pressure to deliver.

Data Security 100

Data Security Metadata MongoDB Scala 100

Precisely

JANUARY 25, 2024

Data Replication Many organizations begin their modernization journey to leverage powerful cloud analytics and decision support tools , including business intelligence, interactive queries, and real-time search. Bespoke data replication solutions developed in-house often fail to deliver the necessary level of metadata management.

Metadata 67

Metadata Data Governance Relational Database Government 67

Monte Carlo

AUGUST 19, 2023

In today’s data-driven landscape, building a data platform is no longer a nice-to-have, but a necessity for most organizations. The five must-have layers of a modern data platform Second to “how do I build my data platform?”, It depends. the most frequent data platform question I get from customers is “where do I start?”

Building 52

Building BI Data Lake Data Governance 52

Monte Carlo

MARCH 1, 2022

Previously, Monte Carlo customers utilized APIs to build on top of our data observability platform. The release of Pycarlo immediately extends the impact and coverage of data observability for our customers, who can now easily aggregate metadata and update logic and monitors across tables in bulk. Aggregating metadata.

Python 52

Python Metadata Business Intelligence Data Engineering 52

Databand.ai

DECEMBER 29, 2022

Quality, Engineering, Security) Frequent keynote speaker, book author, community leader (e.g. Mico’s ability to help companies gain ROI from their business intelligence investments has been sought out by Fortune 500 companies. Her book “Data Visualization for Dummies” is rated as the #7 most influential entrepreneur in BI.

BI 52

BI Consulting Data Science Data Governance 52

Monte Carlo

NOVEMBER 15, 2022

Power BI, Microsoft’s leading business intelligence platform. Power BI gives business teams the ability to visualize data and make critical business decisions, something that just became even easier with Microsoft’s latest announcement for cross-tenant sharing and a new Microsoft 365 integration. Our latest integration?

BI 52

BI Data Warehouse Telecommunication Business Intelligence 52

Monte Carlo

JANUARY 23, 2024

In short, Maxime argues that to effectively scale data science and analytics in the future, data teams needed a specialized engineer to manage ETL, build pipelines, and scale data infrastructure. Enter, the data engineer. As a result, being a data engineer was both a blessing and a curse.

Data Engineering 98

Data Engineering Data Engineer Engineering Data 98

Monte Carlo

JUNE 28, 2022

By design, data was less structured with limited metadata and no ACID properties. Unity Catalog The Unity Catalog unifies metastores, catalogs, and metadata within Databricks. The Databricks Unity Catalog does what it says: it unifies individual metastores, catalogs and serves as a central metadata repository in Databricks.

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

Monte Carlo

JANUARY 23, 2023

In a self-service data landscape, every team wants their business intelligence served up hot and fast. They allow organizations to ingest and manage large volumes of data in an aggregated storage solution when they might not be entirely sure how they’ll use that data in the future, whether for business intelligence or data products.

Data Lake 52

Data Lake Unstructured Data Business Intelligence Architecture 52

Ascend.io

FEBRUARY 15, 2024

Support for Analytics and BI: Continuous replication keeps data in sync for analytics and business intelligence, enabling accurate, up-to-date insights. It is also used on datasets that you plan on creating slowly changing dimensions from and need to build out some historical change data.

Datasets 52

Datasets Database Data Warehouse Data 52

Monte Carlo

SEPTEMBER 23, 2021

Good lineage also collects information about the data (also referred to as metadata) that speaks to governance, business, and technical guidelines associated with specific data tables, serving as a single source of truth for all consumers. Book a time to speak with us using the form below.

BI 52

BI Data Metadata Data Pipeline 52

AltexSoft

OCTOBER 21, 2022

How Apache Kafka streams relate to Franz Kafka’s books. Banks, car manufacturers, marketplaces, and other businesses are building their processes around Kafka to. A subscriber is a receiving program such as an end-user app or business intelligence tool. Practically, nothing. Red Hat , acquired by IBM.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

AltexSoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Monte Carlo

MAY 13, 2021

Here’s how to do that with Snowflake: This query will fetch a list of all tables along with helpful metadata about their settings. This requires building a dedicated data pipeline that you operate, update, and maintain over time. As far as external tables go, we recommend using freshness information from “ SHOW EXTERNAL TABLES… ”.

SQL 40

SQL Metadata Bytes Data Pipeline 40

AltexSoft

MARCH 14, 2023

to build products and services for various purposes. A data stack, in turn, focuses on data : It helps businesses manage data and make the most out of it. It involves converting the raw data into user-friendly models that can be queried by analysts or data scientists to extract insights, build dashboards, or even ML models.

IT 59

IT Data Warehouse Data Governance Data Lake 59

AltexSoft

SEPTEMBER 21, 2023

For instance, you could have different indices for Hotels, Guests, and Bookings in the hospitality industry. Similarly, the Guests index could have documents detailing the information about each guest, like name, contact information, and booking history. Framework Programming The Good and the Bad of Node.js

Engineering 52

Engineering NoSQL Programming Language Java 52

Monte Carlo

APRIL 20, 2023

I can surface ownership metadata and alert the relevant owners to make sure the appropriate changes are made so these breakages never happen. Automated data lineage illustrates how a data freshness incident, for example, can cascade downstream to tables accessed by data warehouse and business intelligence (BI) users.

Data Warehouse 52

Data Warehouse BI Data Government 52

Knowledge Hut

JULY 26, 2023

The tables are linked together by relationships, which build logical links between different types of data. They are commonly used in applications such as data warehousing, business intelligence, and analytics. Go for Web Development course and master frontend, backend, database, and technologies to build scalable website.

Database 52

Database NoSQL Telecommunication MongoDB 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. Inquiring minds want to know.

IT 45

IT Data Lake Business Intelligence Data Architecture 45

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. It took three years for her book “Data Mesh: Delivering Data-Driven Value at Scale” to finally see the world in March 2022.

Architecture 52

Architecture Data Lake Medical Datasets 52

Monte Carlo

AUGUST 17, 2021

Hotjar’s data engineering team supports over 180 stakeholders and their data needs, from deploying models and building pipelines to keeping tabs on data health. To ensure that their data pipelines are reliable and trustworthy, Hotjar relied on dbt for testing and transforming their data before it entered their business intelligence layer.

Insurance 40

Insurance Retail Data Pipeline Portfolio 40

ProjectPro

AUGUST 24, 2021

Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. So, working on a data warehousing project that helps you understand the building blocks of a data warehouse is likely to bring you more clarity and enhance your productivity as a data engineer. You will analyze accidents happening in NYC.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Monte Carlo

MAY 17, 2023

Create Clear Lines of Ownership Build Data Trust With The Business 49. We had low efficiency on internal reporting, and it took a lot of time to build new reports on new metrics.” Being able to quickly identify client-facing issues and be proactive is really the key to building trust in our data. Set Data SLAs 47.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Create Clear Lines of Ownership Build Data Trust With The Business 49. We had low efficiency on internal reporting, and it took a lot of time to build new reports on new metrics.” Being able to quickly identify client-facing issues and be proactive is really the key to building trust in our data. Set Data SLAs 47.

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52