Data Engineering Podcast

DECEMBER 16, 2019

Dataform picks up where your ETL jobs leave off, turning raw data into reliable analytics. Their web based transformation tool with built in collaboration features lets your analysts own the full lifecycle of data in your warehouse. Dataform picks up where your ETL jobs leave off, turning raw data into reliable analytics.

Metadata 100

Metadata PostgreSQL Datasets Data Warehouse 100

ProjectPro

FEBRUARY 25, 2022

Data Ingestion Data Processing Data Splitting Model Training Model Evaluation Model Deployment Monitoring Model Performance Machine Learning Pipeline Tools Machine Learning Pipeline Deployment on Different Platforms FAQs What tools exist for managing data science and machine learning pipelines?

Machine Learning 52

Machine Learning Building Amazon Web Services AWS 52

Monte Carlo

JULY 5, 2023

Nasdaq’s data stack centers around a proprietary ingestion service the company built in 2013 – which means the team has been operating a data warehousing and lake solution in AWS for the better part of a decade. Monte Carlo is equipped with several features that make managing data quality an easy habit rather than a tedious task.

High Quality Data 52

High Quality Data Data Software Engineer Software Engineering 52

Knowledge Hut

NOVEMBER 16, 2023

Cloud computing, along with data science has been the buzzword for quite some time now. Companies have moved towards cloud architecture for their data storage and computing needs. Some of these skills are a part of your data science expertise and the remaining as part of cloud proficiency.

Data Science 52

Data Science Technology Programming Language Cloud Computing 52

Monte Carlo

AUGUST 31, 2023

As the data analyst or engineer responsible for managing this data and making it usable, accessible, and trustworthy, rarely a day goes by without having to field some request from your stakeholders. But what happens when the data is wrong? In our opinion, data quality frequently gets a bad rep.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

ProjectPro

JANUARY 19, 2022

The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis. That needs to be done because raw data is painful to read and work with. Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Monte Carlo

JUNE 28, 2022

Over the past several years, cloud data lakes like Databricks have gotten so powerful (and popular) that according to Mordor Intelligence , the data lake market is expected to grow from $3.74 Traditionally, data lakes held raw data in its native format and were known for their flexibility, speed, and open source ecosystem.

Data Lake 52

Data Lake Metadata AWS Data Warehouse 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.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 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

ProjectPro

JULY 12, 2021

We will now describe the difference between these three different career titles, so you get a better understanding of them: Data Engineer A data engineer is a person who builds architecture for data storage. They can store large amounts of data in data processing systems and convert raw data into a usable format.

Engineering 40

Engineering Deep Learning Software Engineer Software Engineering 40

Knowledge Hut

DECEMBER 22, 2023

Data science uses machine learning algorithms like Random Forests, K-nearest Neighbors, Naive Bayes, Regression Models, etc. They can categorize and cluster raw data using algorithms, spot hidden patterns and connections in it, and continually learn and improve over time. How to Become a Data Scientist in 2024?

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Data Integration 3.Scalability

Hadoop 52

Hadoop Project Big Data Healthcare 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. What is the role of a Data Engineer? Data scientists and data Analysts depend on data engineers to build these data pipelines.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Monte Carlo

FEBRUARY 9, 2023

For those unfamiliar, data vault is a data warehouse modeling methodology created by Dan Linstedt (you may be familiar with Kimball or Imon models ) created in 2000 and updated in 2013. Data vault collects and organizes raw data as underlying structure to act as the source to feed Kimball or Inmon dimensional models.

Architecture 52

Architecture Raw Data Metadata Data Warehouse 52

Knowledge Hut

MARCH 27, 2024

The collection of meaningful market data has become a critical component of maintaining consistency in businesses today. A company can make the right decision by organizing a massive amount of raw data with the right data analytic tool and a professional data analyst. Education technology, training, research, etc.,

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

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

Ascend.io

MAY 18, 2023

In this article, we’ll: Examine the evolution of the data stack Discuss the issues that have arisen from the modern data stack complexity Explore the next steps in the innovation cycle for data engineering The Evolution of the Data Stack Before we dive into the backstory of how we got here, let’s define what a data stack is.

Data Warehouse 52

Data Warehouse Data Pipeline Data Lake Data Engineering 52

ProjectPro

NOVEMBER 30, 2021

This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. The crux of all data-driven solutions or business decision-making lies in how well the respective businesses collect, transform, and store data.

Process 52

Process Data Pipeline Data Warehouse AWS 52

Knowledge Hut

SEPTEMBER 6, 2023

All the data science algorithms and concepts find their implementation in either Python or R. These languages have certain libraries designed specifically for data science specific tasks. Knowing the whereabouts of coding can alleviate the difficulty in understanding these use cases. Eligibility -.There

Data Science 97

Data Science Certification Business Analyst Machine Learning 97

ProjectPro

AUGUST 11, 2021

Since vast amounts of data is present in a data lake, it is ideal for tracking analytical performance and data integration. Data in data lakes may be accessed using SQL, Python, R, Spark or other data querying tools. Hence, data can be kept in data lakes for all times, to be usfurther analyse the data.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

JANUARY 31, 2022

Provides Powerful Computing Resources for Data Processing Before inputting data into advanced machine learning models and deep learning tools, data scientists require sufficient computing resources to analyze and prepare it. Unlock the ProjectPro Learning Experience for FREE How Does Snowflake Store Data Internally?

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

JANUARY 31, 2023

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 52

Big Data Hadoop AWS Relational Database 52

AltexSoft

SEPTEMBER 10, 2021

With it, data is retrieved from its sources, migrated to a staging data repository where it undergoes cleaning and conversion to be further loaded into a target source (commonly data warehouses or data marts ). A newer way to integrate data into a centralized location is ELT. How data consolidation works.

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

Data Engineering Podcast

JANUARY 28, 2018

Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure When you’re ready to launch your next project you’ll need somewhere to deploy it. And I’m the CO executive director of code for science and society, which is the nonprofit that supports that project.

Data 100

Data Project Electronics Data Management 100

Monte Carlo

JUNE 9, 2022

You feel like the world is your oyster and the possibilities for how your data team can add value to the business is virtually infinite. That’s the beauty of Monte Carlo because it allows us to see who is using data and where it is being consumed. He said: First, get all of your data in one place with the highest fidelity.

IT 52

IT Healthcare Raw Data Data Warehouse 52

ProjectPro

JULY 27, 2021

Below are some big data interview questions for data engineers based on the fundamental concepts of big data, such as data modeling, data analysis , data migration, data processing architecture, data storage, big data analytics, etc. What is a decorator?

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 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.

Big Data 52

Big Data Coding Project Hadoop 52

Monte Carlo

MARCH 28, 2023

As part of this movement, Fivetran and dbt fundamentally altered the data pipeline from ETL to ELT. Hightouch interrupted SaaS eating the world in an attempt to shift the center of gravity to the data warehouse. Zero-ETL What it is : A misnomer for one thing; the data pipeline still exists. Pros : Reduced latency.

Data Warehouse 126

Data Warehouse Raw Data Data Pipeline Software Engineer 126

Towards Data Science

APRIL 3, 2023

As part of this movement, Fivetran and dbt fundamentally altered the data pipeline from ETL to ELT. Hightouch interrupted SaaS eating the world in an attempt to shift the center of gravity to the data warehouse. Zero-ETL What it is : A misnomer for one thing; the data pipeline still exists. Pros : Reduced latency.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

AltexSoft

MARCH 14, 2023

That’s why some MDS tools are commercial distributions designed to be low-code or even no-code, making them accessible to data practitioners with minimal technical expertise. This means that companies don’t necessarily need a large data engineering team. Data democratization.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? Below, we share what the “basic” data platform looks like and list some hot tools in each space (you’re likely using several of them): The modern data platform is composed of five critical foundation layers. Data Storage and Processing The first layer?

Building 52

Building BI Data Lake Data Governance 52

ProjectPro

MARCH 14, 2014

It includes the employee's data that ranges from performance histories, survey results to salaries. Enrol for Big Data Online Course to join the Big Data Bandwagon! 14 Hulu Video Delivery 13 machine clusters – 8 cores, 4 TB Used for analysis and log storage 15 Last.fm

Hadoop 40

Hadoop Big Data Data Mining Retail 40

Monte Carlo

JULY 30, 2020

Borrowing Eric Evans’ theory of domain-driven design , a flexible, scalable software development paradigm that matches the structure and language of your code with its corresponding business domain.

IT 45

IT Data Lake Business Intelligence Data Architecture 45