Data Engineering Podcast

SEPTEMBER 25, 2022

Summary Data integration from source systems to their downstream destinations is the foundational step for any data product. With the increasing expecation for information to be instantly accessible, it drives the need for reliable change data capture. In fact, while only 3.5% That’s where our friends at Ascend.io

Food 100

Food MongoDB Scala MySQL 100

Knowledge Hut

NOVEMBER 2, 2023

These Azure data engineer projects provide a wonderful opportunity to enhance your data engineering skills, whether you are a beginner, an intermediate-level engineer, or an advanced practitioner. Who is Azure Data Engineer? Azure SQL Database, Azure Data Lake Storage).

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Data Engineering Podcast

JULY 24, 2022

In this episode Nick Schrock discusses the importance of orchestration and a central location for managing data systems, the road to Dagster’s 1.0 RudderStack helps you build a customer data platform on your warehouse or data lake. In fact, while only 3.5% That’s where our friends at Ascend.io

MongoDB 100

MongoDB Scala MySQL Data Lake 100

Knowledge Hut

MARCH 19, 2024

S3 is suitable across several scenarios that utilize S3’s durability, availability, and security features, such as data archiving, content distribution, and data lake implementations, among many others. The SNS is widely used for broadcasting notifications, triggering workflows, and coordinating distributed systems in real-time.

AWS 52

AWS Cloud Computing Amazon Web Services Relational Database 52

Rockset

JULY 6, 2022

This is the fifth post in a series by Rockset's CTO and Co-founder Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. First, there are many more sources and types of data than there were in the 90s. Most notable are real-time event streams.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Data Engineering Podcast

OCTOBER 9, 2022

In this episode Purvi Shah, the VP of Enterprise Big Data Platforms at American Express, explains how they have invested in the cloud to power this visibility and the complex suite of integrations they have built and maintained across legacy and modern systems to make it possible. In fact, while only 3.5%

Food 100

Food MongoDB Scala MySQL 100

Data Engineering Podcast

JULY 10, 2022

In this episode Chris Riccomini shares his experiences building and scaling data operations at WePay and LinkedIn, as well as the lessons he has learned working with other teams as they automated their own systems. RudderStack helps you build a customer data platform on your warehouse or data lake.

Data Engineering 100

Data Engineering Data Engineer Engineering MongoDB 100

Data Engineering Podcast

NOVEMBER 13, 2022

To make that possible they need a reliable data platform that empowers all of the organization’s stakeholders. In this episode Vishnu Venkataraman shares the journey that he and his team have taken to build and evolve their systems and improve the product offerings that they are able to support. In fact, while only 3.5%

MongoDB 100

MongoDB Scala MySQL Google Cloud 100

Data Engineering Podcast

JULY 3, 2022

In order to quickly identify if and how two data systems are out of sync Gleb Mezhanskiy and Simon Eskildsen partnered to create the open source data-diff utility. report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months. In fact, while only 3.5%

Data Integration 100

Data Integration MongoDB Scala MySQL 100

Data Engineering Podcast

OCTOBER 30, 2022

RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control. In fact, while only 3.5%

Engineering 100

Engineering MongoDB Scala MySQL 100

Data Engineering Podcast

SEPTEMBER 18, 2022

RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control. In fact, while only 3.5%

Hospitality 100

Hospitality Food MongoDB Scala 100

Data Engineering Podcast

AUGUST 6, 2022

Summary The optimal format for storage and retrieval of data is dependent on how it is going to be used. For analytical systems there are decades of investment in data warehouses and various modeling techniques. RudderStack helps you build a customer data platform on your warehouse or data lake.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Data Engineering Podcast

OCTOBER 2, 2022

Summary Data lineage is something that has grown from a convenient feature to a critical need as data systems have grown in scale, complexity, and centrality to business. Alvin is a platform that aims to provide a low effort solution for data lineage capabilities focused on simplifying the work of data engineers.

IT 100

IT Food PostgreSQL MongoDB 100

Snowflake

AUGUST 16, 2023

Custom Event Billing capabilities enable you to build your own pricing strategy. You can charge customers based on their usage and specify billing events based on your preferences, such as consumed rows, ingested rows and more. What remains challenging is how streaming data is brought together with batch data.

Scala 52

Scala Transportation Kafka Data Lake 52

Ascend.io

JANUARY 2, 2024

These are the interfaces where the pipeline taps into various systems to acquire data. The sources of data can be incredibly diverse, ranging from data warehouses, relational databases, and web analytics to CRM platforms, social media tools, and IoT device sensors. In what format will the data be available?

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

Cloudera

AUGUST 26, 2020

With the way systems are set up, if an exchange let it go even for a few minutes it can go completely unchecked with huge financial implications. Flink could be running in the background and defining patterns and analyzing two different events too. From a data ingestion standpoint, NiFi is designed for this purpose.

Banking 87

Banking Data Ingestion Kafka Data Lake 87

Rockset

JULY 28, 2022

As capable as it is, there are still instances where MongoDB alone can't satisfy all of the requirements for an application, so getting a copy of the data into another platform via a change data capture (CDC) solution is required. Debezium It is also possible to capture MongoDB change data capture events using Debezium.

MongoDB 52

MongoDB Kafka NoSQL Data Lake 52

ProjectPro

DECEMBER 7, 2021

Data Pipeline Tools AWS Data Pipeline Azure Data Pipeline Airflow Data Pipeline Learn to Create a Data Pipeline FAQs on Data Pipeline What is a Data Pipeline? Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Rockset

AUGUST 30, 2021

Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. The majority are still draining streaming data into a data lake or a warehouse and are doing batch analytics.

SQL 52

SQL Kafka MongoDB MySQL 52

Knowledge Hut

JUNE 26, 2023

Finnhub API with Kafka for Real-Time Financial Market Data Pipeline Project Overview: The goal of this project is to construct a streaming data pipeline by making use of the real-time financial market data API provided by Finnhub. Additionally, a data pipeline that consumes real-time data will be developed.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Rockset

JULY 29, 2022

Amazon Redshift Amazon Redshift cloud data warehouse is a fully-managed SQL analytics service. It analyzes structured and unstructured data from other warehouses, operational databases, and data lakes. Redshift can scale up to exabytes of storage data, making it an excellent option if you’re handling extensive datasets.

Data Analytics 52

Data Analytics Data Warehouse Datasets Google Cloud 52

Monte Carlo

MARCH 14, 2023

Data ingestion is the process of collecting data from various sources and moving it to your data warehouse or lake for processing and analysis. It is the first step in modern data management workflows. Table of Contents What is Data Ingestion? Decision making would be slower and less accurate.

Data Ingestion 52

Data Ingestion Data Warehouse Lambda Architecture Raw Data 52

Snowflake

APRIL 18, 2024

Legacy security information and event management (SIEM) solutions, like Splunk, are powerful tools for managing and analyzing machine-generated data. Legacy SIEM cost factors to keep in mind Data ingestion: Traditional SIEMs often impose limits to data ingestion and data retention.

Data Lake 80

Data Lake Data Ingestion Bytes Cloud Computing 80

Rockset

OCTOBER 11, 2022

Introduction Managing streaming data from a source system, like PostgreSQL, MongoDB or DynamoDB, into a downstream system for real-time analytics is a challenge for many teams. For a system like Elasticsearch , engineers need to have in-depth knowledge of the underlying architecture in order to efficiently ingest streaming data.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Monte Carlo

APRIL 24, 2023

In this article, we’ll dive deep into the data presentation layers of the data stack to consider how scale impacts our build versus buy decisions, and how we can thoughtfully apply our five considerations at various points in our platform’s maturity to find the right mix of components for our organizations unique business needs.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. The significant difference today is that companies use Apache Kafka as an event streaming platform for building mission-critical infrastructures and core operations platforms.

Kafka 20

Kafka BI SQL Datasets 20

Data Engineering Podcast

JUNE 19, 2022

Summary Metadata is the lifeblood of your data platform, providing information about what is happening in your systems. A variety of platforms have been developed to capture and analyze that information to great effect, but they are inherently limited in their utility due to their nature as storage systems.

Metadata 130

Metadata MongoDB Scala MySQL 130

Rockset

NOVEMBER 6, 2019

Events are messages that are sent by a system to notify operators or other systems about a change in its domain. With event-driven architectures powered by systems like Apache Kafka becoming more prominent, there are now many applications in the modern software stack that make use of events and messages to operate effectively.

Kafka 40

Kafka Data Lake SQL Hadoop 40

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. As the demand for data engineers grows, having a well-written resume that stands out from the crowd is critical.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Cloudera

AUGUST 13, 2021

Every enterprise is trying to collect and analyze data to get better insights into their business. Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis.

Data Pipeline 111

Data Pipeline Data Lake ETL Tools Unstructured Data 111

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? What is data pipeline architecture? Data pipeline architecture is the process of designing how data is surfaced from its source system to the consumption layer. In many cases the data stays in a data lake and is queried from there versus moving to the data warehouse.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

FEBRUARY 8, 2023

It offers a simple and efficient solution for data processing in organizations. It offers users a data integration tool that organizes data from many sources, formats it, and stores it in a single repository, such as data lakes, data warehouses, etc., Create schedules or events that will act as job triggers.

AWS 98

AWS Scala Metadata Data Lake 98

Cloudera

AUGUST 9, 2022

As customers import their mainframe and legacy data warehouse workloads, there is an expectation on the platform that it can meet, if not exceed, the resilience of the prior system and its associated dependencies. The goal is to minimize the impact to a customer’s data-driven decision making in the time of an operational crisis.

Data Lake 81

Data Lake Data Warehouse Architecture Data Ingestion 81

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Data integration , on the other hand, happens later in the data management flow.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Rockset

MARCH 27, 2023

Differing Paradigms Stream processing systems and real-time analytics (RTA) databases are both exploding in popularity. Stream processing systems allow you to aggregate, filter, join, and analyze streaming data. Stream processing systems are rarely used as persistent storage. With that, let’s dive in.

Database 52

Database Process Scala SQL 52

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

JULY 6, 2023

Besides, it offers excellent managing and monitoring capabilities to help system admins and analysts increase productivity. Features The centralized data store integrates data from every system layer. Integrates with Azure Event Hubs, Azure Logic Apps, multiple APIs, and other external event management tools.

Amazon Web Services 52

Amazon Web Services Data Lake Java SQL 52