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.

Data Engineering 52

Data Engineering Data Engineer Engineering 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

Christophe Blefari

JUNE 21, 2024

Both companies have added Data and AI to their slogan, Snowflake used to be The Data Cloud and now they're The AI Data Cloud. 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.

Metadata 147

Metadata Data Warehouse BI Scala 147

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?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 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.

Hadoop 52

Hadoop Project Big Data Healthcare 52

The Pragmatic Engineer

JUNE 13, 2023

For data storage , it uses an object store cluster, running on VAST hardware. In this cluster, around 15 PB of raw data and 21 PB of logical data can be stored. More data can be fitted than there is raw storage available thanks to VAST’s data deduplication.

Cloud 197

Cloud Database Utilities BI 197

Knowledge Hut

APRIL 25, 2023

You can find a comprehensive guide on how data ingestion impacts a data science project with any Data Science course. Why Data Ingestion is Important? Data ingestion provides certain benefits to the business: The raw data coming from various sources is highly complex. Why Data Ingestion is Important?

Data Ingestion 52

Data Ingestion Lambda Architecture Raw Data Kafka 52

Snowflake

MARCH 30, 2023

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse?

Engineering 82

Engineering Raw Data Data Science Scala 82

phData: Data Engineering

SEPTEMBER 27, 2024

Technologies like Apache Kafka, often used in modern CDPs, use log-based approaches to stream customer events between systems in real-time. The raw data is right there, ready to be reprocessed. All this raw data goes into your persistent stage. But the power of logs doesn’t stop there.

Data 52

Data Raw Data Data Lake Architecture 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

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? This is frequently referred to as a 5 or 7 layer (depending on who you ask) data stack like in the image below.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

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.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

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

ProjectPro

AUGUST 11, 2021

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. Kafka streams, consisting of 500,000 events per second, get ingested into Upsolver and stored in AWS S3.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

AltexSoft

SEPTEMBER 23, 2021

Enrichment helps us increase the value of data by adding extra-context. As for the toolset, there are some well-known solutions such as Apache Kafka , a powerful data integration, event-streaming, and data analytics platform. Azure Data Factory. Talend Data Integration. Lumada Data Integration.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

AltexSoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. Data storage and processing. Apache Kafka.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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

MARCH 23, 2015

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization The main motive of the Hadoop 2.0 Earlier there was one Hadoop NameNode for maintaining the tree hierarchy of the HDFS files and tracking the data storage in the cluster. With Hadoop 2.0,

Hadoop 40

Hadoop Big Data Architecture Metadata 40

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 the different platforms from where you can pull data to process visualization? Tableau allows us to connect and pull data from various platforms.

BI 40

BI SQL Database-centric Software Engineer 40

ProjectPro

AUGUST 21, 2015

Data that can be stored in traditional database systems in the form of rows and columns, for example, the online purchase transactions can be referred to as Structured Data. Data that can be stored only partially in traditional database systems, for example, data in XML records can be referred to as semi-structured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

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 meant by Aggregate Functions in SQL?

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

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

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