Data Engineering Podcast

DECEMBER 16, 2019

You work hard to make sure that your data is clean, reliable, and reproducible throughout the ingestion pipeline, but what happens when it gets to the data warehouse? Dataform picks up where your ETL jobs leave off, turning raw data into reliable analytics.

Metadata 100

Metadata PostgreSQL Datasets Data Warehouse 100

Monte Carlo

APRIL 24, 2023

By accommodating various data types, reducing preprocessing overhead, and offering scalability, data lakes have become an essential component of modern data platforms , particularly those serving streaming or machine learning use cases. Not to mention seamless integration with the Oracle ecosystem.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Ascend.io

SEPTEMBER 14, 2023

Python for Data Engineering Use Cases Data engineering, at its core, is about preparing “big data” for analytical processing. It’s an umbrella that covers everything from gathering raw data to processing and storing it efficiently. show() So How Much Python Is Required for a Data Engineer?

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Data Engineering Data Engineer Python Engineering 52

AltexSoft

AUGUST 29, 2023

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. This article explains what a data lake is, its architecture, and diverse use cases. Video explaining how data streaming works.

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Data Lake Architecture IT Amazon Web Services 52

ProjectPro

JUNE 9, 2021

Data Science- Definition Data Science is an interdisciplinary branch encompassing data engineering and many other fields. Data Science involves applying statistical techniques to raw data, just like data analysts, with the additional goal of building business solutions. Machine learning skills.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. However, Apache Kafka is more than just messaging. Some Kafka and Rockset users have also built real-time e-commerce applications , for example, using Rockset’s Java, Node.js

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Kafka BI SQL Hadoop 21

Knowledge Hut

FEBRUARY 27, 2023

Data engineering is also about creating algorithms to access raw data, considering the company's or client's goals. Data engineers can communicate data trends and make sense of the data, which large and small organizations demand to perform major data engineer jobs in Singapore.

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Data Engineering Data Engineer Database-centric Pipeline-centric 52

Knowledge Hut

JUNE 30, 2023

The practice of designing, building, and maintaining the infrastructure and systems required to collect, process, store, and deliver data to various organizational stakeholders is known as data engineering. You can pace your learning by joining data engineering courses such as the Bootcamp Data Engineer.

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Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

DECEMBER 26, 2023

Businesses benefit at large with these data collection and analysis as they allow organizations to make predictions and give insights about products so that they can make informed decisions, backed by inferences from existing data, which, in turn, helps in huge profit returns to such businesses. What is the role of a Data Engineer?

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Data Engineering Data Engineer Engineering Pipeline-centric 98

AltexSoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. The Hadoop toy. So the first secret to Hadoop’s success seems clear — it’s cute. What is Hadoop?

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Hadoop Big Data Google Cloud NoSQL 59

Christophe Blefari

JUNE 21, 2024

One way to read data platforms When we look at platforms history what characterises evolution is the separation (or not) between the engine and the storage. Accordingly to the press Snowflake and Confluent (Kafka) were also trying to buy Tabular. Buying Tabular — Before the last bullet point, it was already something big.

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Metadata Data Warehouse BI Scala 147

ProjectPro

JULY 8, 2021

A detailed introduction to Apache Kafka Architecture, one of the most popular messaging systems for distributed applications. Kafka Streams and Kafka Connect were used to keep track of the threat of the COVID-19 virus and analyze the data for a more thorough response on local, state, and federal levels.

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Kafka Architecture IT Big Data 40

The Pragmatic Engineer

JUNE 13, 2023

The company’s largest data cluster is 20-30PB (petabytes: 1PB is 1,000 terabytes or 1M gigabytes). Ten years ago, this data cluster was 300GB as a Hadoop cluster; that’s around a 100,000-fold increase in data stored! The company runs 4 data centers: in the US and Europe, with two in Asia.

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Cloud Database Utilities BI 197

ProjectPro

APRIL 27, 2016

Scott Gnau, CTO of Hadoop distribution vendor Hortonworks said - "It doesn't matter who you are — cluster operator, security administrator, data analyst — everyone wants Hadoop and related big data technologies to be straightforward. Curious to know about these Hadoop innovations?

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Hadoop Big Data Technology Kafka 40

ProjectPro

SEPTEMBER 26, 2021

As a Big Data Engineer, you shall also know and understand the Big Data architecture and Big Data tools. Hadoop , Kafka , and Spark are the most popular big data tools used in the industry today. You will get to learn about data storage and management with lessons on Big Data tools.

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Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. This architecture shows that simulated sensor data is ingested from MQTT to Kafka.

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Data Engineering Data Engineer Coding Project 52

ProjectPro

MARCH 23, 2015

was intensive and played a significant role in processing large data sets, however it was not an ideal choice for interactive analysis and was constrained for machine learning, graph and memory intensive data analysis algorithms. In one of our previous articles we had discussed about Hadoop 2.0

Hadoop 40

Hadoop Big Data Architecture Metadata 40

ProjectPro

AUGUST 11, 2021

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? ironSource has to collect and store vast amounts of data from millions of devices. ironSource started making use of Upsolver as its data lake for storing raw event data.

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Data Lake Data Warehouse Cloud Hadoop 52

Rockset

FEBRUARY 6, 2019

That meant a system that was sufficiently nimble and powerful to execute fast SQL queries on raw data, essentially performing any needed transformations as part of the query step, and not as part of a complex data pipeline. It indexes all data as and when it arrives via the Tailer. We chose ALT for Rockset.

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Lambda Architecture Architecture MongoDB Kafka 40

ProjectPro

AUGUST 21, 2015

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. What is the difference between Hadoop and Traditional RDBMS?

Hadoop 40

Hadoop Big Data Metadata Java 40

AltexSoft

MAY 14, 2021

Modern technologies allow gathering both structured (data that comes in tabular formats mostly) and unstructured data (all sorts of data formats) from an array of sources including websites, mobile applications, databases, flat files, customer relationship management systems (CRMs), IoT sensors, and so on. Apache Hadoop.

Big Data 78

Big Data Data Analytics IT NoSQL 78

LinkedIn Engineering

APRIL 4, 2023

System Architecture Overview Setup We wanted to build a single data processing pipeline that would be efficient and scalable as more metrics are added. The data needed to compute our metrics came from various sources including MySQL databases, Kafka topics and Hadoop (HDFS). from the metric’s processing logic (i.e.

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MySQL Datasets Software Engineer Software Engineering 122

Confluent

OCTOBER 16, 2019

Trains are an excellent source of streaming data—their movements around the network are an unbounded series of events. Using this data, Apache Kafka ® and Confluent Platform can provide the foundations for both event-driven applications as well as an analytical platform. As with any real system, the data has “character.”

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Kafka Building Data Coding 19

AltexSoft

NOVEMBER 10, 2021

The DW nature isn’t the best fit for complex data processing such as machine learning as warehouses normally store task-specific data, while machine learning and data science tasks thrive on the availability of all collected data. Another type of data storage — a data lake — tried to address these and other issues.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Monte Carlo

JUNE 14, 2023

5 Data pipeline architecture designs and their evolution The Hadoop era , roughly 2011 to 2017, arguably ushered in big data processing capabilities to mainstream organizations. Data then, and even today for some organizations, was primarily hosted in on-premises databases with non-scalable storage.

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Data Pipeline Architecture Data Lake Data Warehouse 52

Rockset

MAY 8, 2023

It also provides support for Spark, Hadoop, and Python, making it convenient for the machine learning team to adopt and utilize. For each user, they collected and maintained in real time, using Kafka, a short-term history of user clicks and skips in the last two weeks. The workflow for vector search at eBay.

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Metadata Algorithm Datasets Google Cloud 52

ProjectPro

JUNE 24, 2021

Data Cleaning: To improve the data quality and filter the noisy, inaccurate, and irrelevant data for analysis, data cleaning is a key skill needed for all analytics job roles. Microsoft Excel: A successful Excel spreadsheet helps to organize raw data into a more readable format.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

ProjectPro

APRIL 15, 2016

Preparing for a Hadoop job interview then this list of most commonly asked Apache Pig Interview questions and answers will help you ace your hadoop job interview in 2018. Research and thorough preparation can increase your probability of making it to the next step in any Hadoop job interview.

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Hadoop Java Big Data SQL 40

ProjectPro

NOVEMBER 30, 2021

Now that we have understood how much significant role data plays, it opens the way to a set of more questions like How do we acquire or extract raw data from the source? How do we transform this data to get valuable insights from it? Where do we finally store or load the transformed data? along with ETL.

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

JULY 27, 2021

It involves creating a visual representation of an entire system of data or a part of it. The process of data modeling begins with stakeholders providing business requirements to the data engineering team. Data warehouse Operational database Data warehouses generally support high-volume analytical data processing - OLAP.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

DECEMBER 22, 2016

We have collected a library of solved Data Science use-case code examples that you can find here. When being interviewed for a data analyst job role, candidates want to do everything that can let the interviewer see their communication skills, analytical skills and problem solving abilities. We add new use-cases every week.

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Data Mining Data Cleanse Datasets Data Analysis 52

ProjectPro

AUGUST 18, 2021

By the end of 2022, the industry will experience a huge demand for data analysts, data scientists, and BI professionals with decent Tableau knowledge. What are discrete and continuous data in Tableau? Tableau helps represent data in two different forms. What does Tableau's analytics pane give us?

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BI SQL Database-centric Software Engineer 40

ProjectPro

MAY 31, 2021

To build a big data project, you should always adhere to a clearly defined workflow. Before starting any big data project, it is essential to become familiar with the fundamental processes and steps involved, from gathering raw data to creating a machine learning model to its effective implementation.

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Big Data Coding Project Hadoop 52

AltexSoft

MARCH 14, 2023

Additionally, this modularity can help prevent vendor lock-in, giving organizations more flexibility and control over their data stack. Many components of a modern data stack (such as Apache Airflow, Kafka, Spark, and others) are open-source and free. But this distinction has been blurred with the era of cloud data warehouses.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Rockset

APRIL 15, 2022

Explosion in Streaming Data Before Kafka, Spark and Flink, streaming came in two flavors: Business Event Processing (BEP) and Complex Event Processing (CEP). Many (Kafka, Spark and Flink) were open source. It also prevents data bloat that would hamper storage efficiency and query speeds.

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Analytics Application Data Warehouse Kafka Raw Data 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. 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.

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Scala Data Lake BI Google Cloud 64