AltexSoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Edureka

FEBRUARY 8, 2024

Whether you are hosting a website, running complex data analytics, or deploying machine learning models, the instance type serves as the foundation upon which your entire AWS architecture is built. In-Memory Caching- Memory-optimized instances are suitable for in-memory caching solutions, enhancing the speed of data access.

AWS 52

AWS NoSQL Deep Learning Datasets 52

AltexSoft

JUNE 7, 2021

The framework provides a way to divide a huge data collection into smaller chunks and shove them across interconnected computers or nodes that make up a Hadoop cluster. As a result, a Big Data analytics task is split up, with each machine performing its own little part in parallel. Data storage options. scalability.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JANUARY 31, 2023

In this blog, we'll dive into some of the most commonly asked big data interview questions and provide concise and informative answers to help you ace your next big data job interview. Get ready to expand your knowledge and take your big data career to the next level! “Data analytics is the future, and the future is NOW!

Big Data 52

Big Data Hadoop AWS Relational Database 52

Knowledge Hut

DECEMBER 26, 2023

After carefully exploring what we mean when we say "big data," the book explores each phase of the big data lifecycle. With Tableau, which focuses on big data visualization , you can create scatter plots, histograms, bar, line, and pie charts.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

Knowledge Hut

DECEMBER 26, 2023

Pipeline-centric Pipeline-centric data engineers work with Data Scientists to help use the collected data and mostly belong in midsize companies. Database-centric In bigger organizations, Data engineers mainly focus on data analytics since the data flow in such organizations is huge.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer is someone proficient in a variety of programming languages and frameworks, such as Python, SQL, Scala, Hadoop, Spark, etc. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes. NoSQL databases are often implemented as a component of data pipelines.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Edureka

FEBRUARY 7, 2023

Dynamic data masking serves several important functions in data security. Azure Synapse Interview Questions – Analytics The interview questions and responses for azure data engineers for synapse analytics and stream analytics are covered in this section. 21) What are databases with multiple models?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Silectis

JANUARY 3, 2021

Data Science Data science is a practice that uses scientific methods, algorithms and systems to find insights within structured and unstructured data. Data Visualization Graphic representation of a set or sets of data. Data Warehouse A storage system used for data analysis and reporting.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

JULY 29, 2022

Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. a suitable technology to implement data lake architecture. As a result, today we have a huge ecosystem of interoperable instruments addressing various challenges of Big Data.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

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

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. HBase helps perform fast read/writes.

Architecture 40

Architecture IT Hadoop NoSQL 40

AltexSoft

MARCH 14, 2023

Databases store key information that powers a company’s product, such as user data and product data. The ones that keep only relational data in a tabular format are called SQL or relational database management systems (RDBMSs). Data storage component in a modern data stack.

IT 59

IT Data Warehouse Data Governance Data Lake 59

ProjectPro

FEBRUARY 16, 2023

In fact, approximately 70% of professional developers who work with data (e.g., data engineer, data scientist , data analyst, etc.) According to the 8,786 data professionals participating in Stack Overflow's survey, SQL is the most commonly-used language in data science. use SQL, compared to 61.7%

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

ProjectPro

NOVEMBER 15, 2021

It incorporates caching, stream computing, message queuing, and other functionalities to decrease the complexity and expenses of development and operations, in addition to the 10x quicker time-series database. DataFrames are used by Spark SQL to accommodate structured and semi-structured data.

Big Data 52

Big Data Project Metadata Programming Language 52

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., They enable the connection of various data sources to the Hadoop environment.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

JANUARY 19, 2022

Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Companies frequently hire certified Azure Data Engineers to convert unstructured data into useful, structured data that data analysts and data scientists can use.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

JULY 27, 2021

Also, you will find some interesting data engineer interview questions that have been asked in different companies (like Facebook, Amazon, Walmart, etc.) that leverage big data analytics and tools. Preparing for data engineer interviews makes even the bravest of us anxious. Structured data usually consists of only text.

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. In the data transformation we saw lot of limitation with this kind of BI architecture.

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40

ProjectPro

JUNE 23, 2016

Users can import one or more tables, the entire database to selected columns from a table using Apache Sqoop. Sqoop is compatible with all JDBC compatible databases. When importing data, Sqoop controls the number of mappers accessing RDBMS to avoid distributed denial of service attacks.

Hadoop 40

Hadoop MySQL Relational Database Java 40

ProjectPro

NOVEMBER 14, 2015

Apache Hadoop and Apache Spark fulfill this need as is quite evident from the various projects that these two frameworks are getting better at faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Data Migration 2.

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

OCTOBER 15, 2014

Directly leverages SQL and is easy to learn for database experts. 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.

Hadoop 52

Hadoop Unstructured Data Java SQL 52