Knowledge Hut

DECEMBER 26, 2023

This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc. Hadoop is the second most important skill for a Data engineer.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

AUGUST 11, 2021

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Knowledge Hut

JANUARY 30, 2024

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

ProjectPro

APRIL 4, 2015

With the help of our best in class Hadoop faculty, we have gathered top Hadoop developer interview questions that will help you get through your next Hadoop job interview. IT organizations from various domains are investing in big data technologies, increasing the demand for technically competent Hadoop developers.

Hadoop 40

Hadoop Big Data Recruitment Java 40

Edureka

AUGUST 2, 2023

The ease with which data analysis workflows may be documented and shared thanks to its seamless integration with other well-liked data science tools, such as Jupyter Notebooks.Python’s adaptability goes beyond just data analysis and manipulation, too. Data scientists use SQL to query, update, and manipulate data.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

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

Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. The Replication Manager support matrix is documented in our public docs.

Cloud 73

Cloud Data Lake Cloud Storage Metadata 73

Knowledge Hut

SEPTEMBER 26, 2023

Effective Data Storage: Azure Synapse offers robust data storage solutions that cater to the needs of modern data-driven organizations. It provides the infrastructure necessary for efficient data storage and management, enabling you to store and access large volumes of data reliably.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Edureka

FEBRUARY 9, 2023

In this blog on “Azure data engineer skills”, you will discover the secrets to success in Azure data engineering with expert tips, tricks, and best practices Furthermore, a solid understanding of big data technologies such as Hadoop, Spark, and SQL Server is required. Who is an Azure Data Engineer?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

MARCH 14, 2014

Big Data analysis will be about building systems around the data that is generated. Every department of an organization including marketing, finance and HR are now getting direct access to their own data. Studies show, that by 2020, 80% of all Fortune 500 companies will have adopted Hadoop.

Hadoop 40

Hadoop Big Data Data Mining Retail 40

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

NOVEMBER 15, 2021

When any particular project is open-sourced, it makes the source code accessible to anyone. The adaptability and technical superiority of such open-source big data projects make them stand out for community use. DataFrames are used by Spark SQL to accommodate structured and semi-structured data.

Big Data 52

Big Data Project Metadata Programming Language 52

Towards Data Science

MARCH 5, 2024

The storage system is using Capacitor, a proprietary columnar storage format by Google for semi-structured data and the file system underneath is Colossus, the distributed file system by Google. More information about this can be found in the official search index documentation. The standard model is straightforward.

Bytes 67

Bytes Google Cloud Cloud Storage Utilities 67

ProjectPro

JULY 22, 2016

The desire to save every bit and byte of data for future use, to make data-driven decisions is the key to staying ahead in the competitive world of business operations. All this is possible due to the low cost storage systems like Hadoop and Amazon S3.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

ProjectPro

DECEMBER 17, 2021

Industry experts at ProjectPro say that although both have been developed for the same task, i.e., data storage, they vary significantly in terms of the audience they cater to. NoSQL databases are designed to store unstructured data like graphs, documents, etc., whereas SQL databases deal with structured data in tables.

Data Science 52

Data Science SQL NoSQL Programming Language 52

Monte Carlo

JUNE 14, 2023

This frequently involves, in some order, extraction (from a source system), transformation (where data is combined with other data and put into the desired format), and loading (into storage where it can be accessed). Most organizations deploy some or all of these data pipeline architectures.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

JUNE 6, 2015

Solocal has taken big data to the next stage of BI by designing a novel vision of BI with the open source distributed computing framework Hadoop. It replaced its traditional BI structure by integrating big data and Hadoop."-April The goal of BI is to create intelligence through Data. So what is BI?

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

ProjectPro

JANUARY 25, 2022

When it comes to data ingestion pipelines, PySpark has a lot of advantages. PySpark allows you to process data from Hadoop HDFS , AWS S3, and various other file systems. To access the configuration value, use get(key, defaultValue=None). With PySparkSQL, we can also use SQL queries to perform data extraction.

Big Data 52

Big Data Data Process Process Kafka 52

ProjectPro

AUGUST 24, 2021

Google BigQuery receives the structured data from workers. Finally, the data is passed to Google Data studio for visualization. Learn how to process Wikipedia archives using Hadoop and identify the lived pages in a day. Understand the importance of Qubole in powering up Hadoop and Notebooks.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

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?

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

DECEMBER 10, 2021

Azure Cloud Services are hosted on virtual machines, and they let one have a higher degree of control over the VMs by allowing software installation on the VMs and also making them remotely accessible. A user only pays for the resources he needs from a cloud service provider and accesses them over a secure Internet connection.

BI 52

BI Cloud Computing SQL Database 52

ProjectPro

MARCH 19, 2015

With increasing size of the database or increasing number of users, Relational Database Management Systems using SQL suffer from serious performance bottlenecks -making real time unstructured data processing a hard row to hoe. NoSQL database can be referred to as structured storage which consists of relational database as the subset.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

ProjectPro

AUGUST 18, 2021

. · Tableau also provides a data blending facility. Which Tableau data types are preferable while dealing with structured data? We can prefer using Text (string) values and numerical values as the two popular data types while dealing with structured data in Tableau.

BI 40

BI Database-centric SQL Software Engineer 40

ProjectPro

JANUARY 19, 2022

Azure Data Engineer Job Description | Accenture Azure Certified Data Engineer Azure Data Engineer Certification Microsoft Azure Projects for Practice to Enhance Your Portfolio FAQs Who is an Azure Data Engineer? This is where the Azure Data Engineer enters the picture.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

JULY 18, 2023

Spark SQL brings native support for SQL to Spark and streamlines the process of querying semistructured and structured data. Datasets: RDDs can contain any type of data and can be created from data stored in local filesystems, HDFS (Hadoop Distributed File System), databases, or data generated through transformations on existing RDDs.

Big Data 52

Big Data Data Process Process Hadoop 52

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Netflix Tech

DECEMBER 14, 2018

In the previous blog posts in this series, we introduced the N etflix M edia D ata B ase ( NMDB ) and its salient “Media Document” data model. A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve.

Media 94

Media Database Metadata Data Schemas 94

Cloudera

OCTOBER 3, 2018

First, remember the history of Apache Hadoop. Google built an innovative scale-out platform for data storage and analysis in the late 1990s and early 2000s, and published research papers about their work. The two of them started the Hadoop project to build an open-source implementation of Google’s system.

Hadoop 75

Hadoop Cloud Data Storage Big Data 75

AltexSoft

MAY 14, 2021

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. Data storage and processing.

Big Data 78

Big Data Data Analytics IT NoSQL 78

AltexSoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Key features of a data lakehouse. Unstructured and streaming data support.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

MAY 12, 2023

Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. Unlike structured data, which is organized into neat rows and columns within a database, unstructured data is an unsorted and vast information collection.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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.

Scala 64

Scala Data Lake BI Google Cloud 64