Knowledge Hut

APRIL 25, 2023

Strong programming skills: Data engineers should have a good grasp of programming languages like Python, Java, or Scala, which are commonly used in data engineering. Database management: Data engineers should be proficient in storing and managing data and working with different databases, including relational and NoSQL databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

MARCH 15, 2024

Making decisions in the database space requires deciding between RDBMS (Relational Database Management System) and NoSQL, each of which has unique features. RDBMS uses SQL to organize data into structured tables, whereas NoSQL is more flexible and can handle a wider range of data types because of its dynamic schemas.

NoSQL 52

NoSQL Database-centric Relational Database PostgreSQL 52

Ascend.io

NOVEMBER 21, 2023

Extract The initial stage of the ELT process is the extraction of data from various source systems. This phase involves collecting raw data from the sources, which can range from structured data in SQL or NoSQL servers, CRM and ERP systems, to unstructured data from text files, emails, and web pages.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Knowledge Hut

MAY 4, 2023

Data engineering is all about data storage and organizing and optimizing warehouses plus databases. It helps organizations understand big data and helps in collecting, storing, and analyzing vast amounts of data, using technical skills related to NoSQL, SQL, and hybrid infrastructures.

Data Engineering 52

Data Engineering Data Engineer Engineering Banking 52

Silectis

JANUARY 3, 2021

If you’re new to data engineering or are a practitioner of a related field, such as data science, or business intelligence, we thought it might be helpful to have a handy list of commonly used terms available for you to get up to speed. Data Visualization Graphic representation of a set or sets of data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JUNE 6, 2015

Business Intelligence (BI) combines human knowledge, technologies like distributed computing, and Artificial Intelligence, and big data analytics to augment business decisions for driving enterprise’s success. It also detects any problems that might be there in the data – so there is some data quality layer.

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

ProjectPro

OCTOBER 15, 2014

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Hadoop technology is the buzz word these days but most of the IT professionals still are not aware of the key components that comprise the Hadoop Ecosystem. Pig is SQL like but varies to a great extent.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

Knowledge Hut

JULY 24, 2023

Disruptive database technologies include, for instance: Blockchain Blockchain is a distributed ledger technology that enables data to be safely stored across several nodes in a decentralized (or sometimes in a centralized) manner. These nodes contain hashed/encrypted information to ensure security at each level.

Database 52

Database NoSQL Management Relational Database 52

ProjectPro

NOVEMBER 14, 2015

As we step into the latter half of the present decade, we can’t help but notice the way Big Data has entered all crucial technology-powered domains such as banking and financial services, telecom, manufacturing, information technology, operations, and logistics.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

MARCH 19, 2015

Big Data NoSQL databases were pioneered by top internet companies like Amazon, Google, LinkedIn and Facebook to overcome the drawbacks of RDBMS. RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

ProjectPro

AUGUST 6, 2015

Amazon is collecting intelligence and valuable pricing information (big data) from its competitors. Amazon uses big data to operate effectively in a fast-paced and competitive e-commerce environment where price and online advertisements dominate. Sports brands like ESPN have also got on to the big data bandwagon.

Big Data 52

Big Data Hadoop Insurance Media 52

AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

MARCH 27, 2024

What Is Big Data Analytics? An organization can make informed decisions based on a big data analytics platform, which works by uncovering patterns, correlations, customer preferences and market trends hidden in the data. Some open-source technology for big data analytics are : Hadoop. Apache Spark. Apache Storm.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Grouparoo

DECEMBER 26, 2021

For data storage, the database is one of the fundamental building blocks. They provide a method for storing information in an organized manner that ensures it remains accessible while providing the mechanisms to protect the integrity, confidentiality, and availability of the information they hold.

Database 52

Database NoSQL Relational Database Data Storage 52

Knowledge Hut

DECEMBER 26, 2023

If you continue tracking these data points for over six months or a year, you will be able to gather more information about your sleeping patterns; when do you have short-awakenings at night, when do you sleep the most, how long do you sleep on holidays, etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

OCTOBER 24, 2023

This involves listening attentively, asking the right questions, and being able to summarize information. SQL and SQL Server BAs must deal with the organization's structured data. They ought to be familiar with databases like Oracle DB, NoSQL, Microsoft SQL, and MySQL.

Business Analyst 98

Business Analyst Business Intelligence SQL Programming Language 98

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

AltexSoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. The truth is, there’s more to this term than just the size of information generated. Variety is the vector showing the diversity of Big Data. Data storage and processing.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Edureka

FEBRUARY 7, 2023

In this case, the service provider creates a managed service that allows users to access these services on demand. Dynamic data masking serves several important functions in data security. It restricts sensitive information to a small group of users. Data export and archiving to outside data stores are supported.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

AltexSoft

JULY 29, 2022

How HDFS master-slave structure works. A master node called NameNode maintains metadata with critical information, controls user access to the data blocks, makes decisions on replications, and manages slaves. You store all the information in HDFS without pre-processing and decide on the schema to apply to it later.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

JUNE 7, 2021

They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. But which one of the celebrities should you entrust your information assets to? You don’t need to archive or clean data before loading. How does it work? scalability.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JANUARY 31, 2023

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! Everything is about data these days. RDBMS stores structured data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two.

Architecture 52

Architecture Data Lake Medical Datasets 52

ProjectPro

JANUARY 24, 2023

With BigQuery, users can process and analyze petabytes of data in seconds and get insights from their data quickly and easily. Moreover, BigQuery offers a variety of features to help users quickly analyze and visualize their data. It provides powerful query capabilities for running SQL queries to access and analyze data.

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

AltexSoft

OCTOBER 8, 2021

What’s more, that data comes in different forms and its volumes keep growing rapidly every day — hence the name of Big Data. The good news is, businesses can choose the path of data integration to make the most out of the available information. Data integration in a nutshell. high security.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

AltexSoft

JULY 27, 2021

At the same time, the continuous growth of available data has led to information overload — when there are too many choices, complicating decision-making. Recommender systems , also known as recommender engines, are information filtering systems that provide individual recommendations in real-time. Data sparsity.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

Cloudera

APRIL 2, 2019

HBase is a distributed, scalable NoSQL database that enterprises use to power applications that need random, real time read/write access to semi-structured data. For more information learn how to get data insights faster from bigger workloads with Intel® Optane DC persistent memory.

NoSQL 48

NoSQL Google Cloud Hadoop Machine Learning 48

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

Cloudera

JANUARY 22, 2019

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge. Data orchestration.

Big Data 44

Big Data NoSQL Data Lake Hadoop 44

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

AUGUST 24, 2016

The NOSQL column oriented database has experienced incredible popularity in the last few years. HBase is a NoSQL , column oriented database built on top of hadoop to overcome the drawbacks of HDFS as it allows fast random writes and reads in an optimized way. . If you need random access, you have to have HBase."-

Architecture 40

Architecture IT Hadoop NoSQL 40

ProjectPro

OCTOBER 28, 2015

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc.,

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

Netflix Tech

DECEMBER 14, 2018

under varying load conditions as well as a wide variety of access patterns; (b) scalability?—?persisting data access semantics that guarantee repeatable data read behavior for client applications. data access semantics that guarantee repeatable data read behavior for client applications.

Media 94

Media Database Metadata Data Schemas 94

ProjectPro

APRIL 26, 2016

Pig vs Hive Criteria Pig Hive Type of Data Apache Pig is usually used for semi structured data. Used for Structured Data Schema Schema is optional. Language It is a procedural data flow language. HBase is a NoSQL database. Hcatalog can be used to share data structures with external systems.

Hadoop 40

Hadoop Metadata SQL Database 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

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. txt), Microsoft Word documents (.doc,docx),

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40