Knowledge Hut

JUNE 16, 2023

In today's data-driven world, organizations are trying to find valuable insights from the vast sets of data available to them. That is where Data analytics comes into the picture - guiding organizations to make smarter decisions by utilizing statistical and computational methods. What is Data Analytics?

Programming Language 52

Programming Language Cloud Computing Data Preparation Data Science 52

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

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

ProjectPro

SEPTEMBER 9, 2021

Spark SQL, for instance, enables structured data processing with SQL. Apache Hive and Apache Spark are two popular big data tools for data management and Big Data analytics. The tool offers a rich interface with easy usage by offering APIs in numerous languages, such as Python, R, etc.

Hadoop 52

Hadoop Big Data Tools Java SQL 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. What Is Big Data Analytics?

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 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

Knowledge Hut

FEBRUARY 16, 2023

After the inception of databases like Hadoop and NoSQL, there's a constant rise in the requirement for processing unstructured or semi-structured data. Data Engineers are responsible for these tasks. However, when it comes to the best lucrative career, the USA is the preferred location.

Data Engineering 52

Data Engineering Data Engineer Engineering Healthcare 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

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

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

AltexSoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

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Big Data Data Analytics IT NoSQL 78

ProjectPro

AUGUST 6, 2015

Companies like Electronic Arts, Riot Games are using big data for keeping a track of game play which helps predict performance of the play by analysing 4TB of operational logs and 500GB of structured data. Sports brands like ESPN have also got on to the big data bandwagon.

Big Data 52

Big Data Hadoop Insurance Media 52

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

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

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

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

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

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

Knowledge Hut

OCTOBER 24, 2023

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. BAs can store and process massive volumes of data with the use of these databases. They can access, retrieve, manipulate, and analyze data using this.

Business Analyst 98

Business Analyst Business Intelligence SQL Programming Language 98

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

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. 15) What is Azure table storage, exactly?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

ProjectPro

JANUARY 24, 2023

The three essential functions of combining Google Analytics and BigQuery include- 1) Data Manipulation BigQuery allows for data manipulation and transformation, such as filtering, joins, and aggregations, which helps to prepare the data for analysis and visualization. Q: Is BigQuery SQL or NoSQL?

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

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

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

Cloudera

APRIL 2, 2019

Cloudera and Intel have a long history of innovation, driving big data analytics and machine learning into the enterprise with unparalleled performance and security. Apache HBase® is one of many analytics applications that benefit from the capabilities of Intel Optane DC persistent memory.

NoSQL 48

NoSQL Google Cloud Hadoop Machine Learning 48

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.

Big Data 45

Big Data NoSQL Data Lake Hadoop 45

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

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

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., However, it is not very suitable for queries requiring low latency or interactive queries.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

NOVEMBER 15, 2021

1/5 hardware/cloud service costs, full-stack for time-series data, robust data analysis, seamless integration with other tools, zero management, and no learning curve are the significant highlights of TDengine. DataFrames are used by Spark SQL to accommodate structured and semi-structured data.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

DECEMBER 10, 2021

It is a cloud-based NoSQL database that deals mainly with modern app development. CosmosDB data can be easily shared and replicated anywhere in the world, which ensures faster and more efficient app development. Azure Table Storage- Azure Tables is a NoSQL database for storing structured data without a schema.

BI 52

BI Cloud Computing SQL Database 52

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. Hive requires a well-defined Schema. HBase runs on top of HDFS.

Hadoop 40

Hadoop Metadata SQL Database 40

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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 23, 2016

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Apache Sqoop uses Hadoop MapReduce to get data from relational databases and stores it on HDFS. Structured datastores indicate that Sqoop only works with Relational Database Management Systems (RDBMS).

Hadoop 40

Hadoop MySQL Relational Database Java 40

ProjectPro

APRIL 27, 2016

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization These challenges opened the road to an efficient high-level language for Hadoop i.e. PigLatin, which was developed at Yahoo. It is difficult to manage n-stage jobs with Hadoop MapReduce.

Hadoop 40

Hadoop Big Data Technology Big Data Tools 40

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