Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. This information is gathered from a variety of sources, including sensor readings, social media engagements, and client transactions. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly.

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Data Process Process Data Cleanse Data Mining 52

phData: Data Engineering

SEPTEMBER 19, 2023

This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake? What are Data Modeling Methodologies, and Why Are They Important for a Data Lake?

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AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. Structured data sources.

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Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

JULY 24, 2023

NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data.

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Database NoSQL Management Relational Database 52

Towards Data Science

FEBRUARY 15, 2023

Concepts, theory, and functionalities of this modern data storage framework Photo by Nick Fewings on Unsplash Introduction I think it’s now perfectly clear to everybody the value data can have. To use a hyped example, models like ChatGPT could only be built on a huge mountain of data, produced and collected over years.

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Data Lake Data Warehouse Hadoop Data Architecture 80

Knowledge Hut

MARCH 7, 2024

Data analytics tools in big data includes a variety of tools that can be used to enhance the data analysis process. These tools include data analysis, data purification, data mining, data visualization, data integration, data storage, and management.

Big Data 52

Big Data Data Analytics Data Mining MongoDB 52

AltexSoft

JUNE 26, 2023

Find sources of relevant data. Choose data collection methods and tools. Decide on a sufficient data amount. Set up data storage technology. Below, we’ll elaborate on each step one by one and share our experience of data collection. Key differences between structured, semi-structured, and unstructured data.

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Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

MARCH 14, 2023

It must collect, analyze, and leverage large amounts of customer data from various sources, including booking history from a CRM system, search queries tracked with Google Analytics, and social media interactions. Data sources component in a modern data stack. Data storage component in a modern data stack.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Knowledge Hut

JULY 26, 2023

This velocity aspect is particularly relevant in applications such as social media analytics, financial trading, and sensor data processing. Variety: Variety represents the diverse range of data types and formats encountered in Big Data. Handling this variety of data requires flexible data storage and processing methods.

Big Data 52

Big Data Data Cleanse Retail Healthcare 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.

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Big Data Data Mining Business Intelligence Machine Learning 75

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. Variety is the vector showing the diversity of Big Data.

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Knowledge Hut

MARCH 22, 2024

To explain linear and non-linear data structure, linear structures organize data in a straightforward, sequential manner, while non-linear structures manage data in a more complex, often hierarchical way. Memory Use: Each utilises computer memory for data storage, though the approach may differ.

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Edureka

JANUARY 18, 2024

Introduction of R as an optional language in data science, highlighting its strengths in statistics and visualization. Data Manipulation Examine the most important data manipulation libraries like explore Pandas for structured data manipulation and Numpy for numerical operations in Python.

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Data Science Deep Learning NoSQL Machine Learning 40

ProjectPro

MAY 31, 2021

And even if you’re not very active on social media, I’m sure you now and then check your phone before leaving the house to see what the traffic is like on your route to know how long it could take you to reach your destination. Spark has a Streaming tool that can process real-time streaming data.

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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

MARCH 27, 2024

Data analytics tools in big data includes a variety of tools that can be used to enhance the data analysis process. These tools include data analysis, data purification, data mining, data visualization, data integration, data storage, and management.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Knowledge Hut

MAY 31, 2023

Companies utilize different approaches to deal with data in order to extract information from structured, semi-structured, or unstructured data sets. Business Intelligence is one such approach that helps professionals to extract valuable information from structured data.

Business Intelligence 52

Business Intelligence BI Business Analyst Consulting 52

Rockset

SEPTEMBER 20, 2022

Other companies store all the smart contract data in one table and then use aggregation frameworks to simplify the data storage. Image Source Regardless of the approach, these companies typically expose the data to users by allowing them to write custom SQL queries.

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PostgreSQL MongoDB SQL Datasets 52

Edureka

JUNE 1, 2023

percent of the world’s population, were social media users. The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching 64.2 Over the next five years up to 2025 , global data creation is projected to grow to more than 180 zettabytes. As of January 2023, there were 5.16

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AWS Data Analytics Cloud Amazon Web Services 52

AltexSoft

NOVEMBER 10, 2021

The data in this case is checked against the pre-defined schema (internal database format) when being uploaded, which is known as the schema-on-write approach. Purpose-built, data warehouses allow for making complex queries on structured data via SQL (Structured Query Language) and getting results fast for business intelligence.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

JULY 18, 2023

Spark SQL brings native support for SQL to Spark and streamlines the process of querying semistructured and structured data. For instance, social media platforms may use GraphX to analyze user connections and suggest potential friends. It works with various formats, including Avro, Parquet, ORC, and JSON.

Big Data 52

Big Data Data Process Process Hadoop 52

Knowledge Hut

JANUARY 18, 2024

4 Purpose Utilize the derived findings and insights to make informed decisions The purpose of AI is to provide software capable enough to reason on the input provided and explain the output 5 Types of Data Different types of data can be used as input for the Data Science lifecycle.

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Knowledge Hut

DECEMBER 26, 2023

Analyzing more data points will therefore give you a more detailed insight into your study. The spectrum of sources from which data is collected for the study in Data Science is broad. It comes from numerous sources ranging from surveys, social media platforms, e-commerce websites, browsing searches, etc.

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Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

NOVEMBER 15, 2021

With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing. DataFrames are used by Spark SQL to accommodate structured and semi-structured data. Calcite has chosen to stay out of the data storage and processing business.

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Big Data Project Metadata Programming Language 52

ProjectPro

MARCH 14, 2014

Organizations across the world are excited about big data and customer analytics not just because the data are big but the potential for companies using big data is huge. 14 Hulu Video Delivery 13 machine clusters – 8 cores, 4 TB Used for analysis and log storage 15 Last.fm

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Hadoop Big Data Data Mining Retail 40

ProjectPro

MARCH 15, 2016

Hadoop is beginning to live up to its promise of being the backbone technology for Big Data storage and analytics. Companies across the globe have started to migrate their data into Hadoop to join the stalwarts who already adopted Hadoop a while ago. Hadoop allows us to store data that we never stored before.

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Hadoop Retail Healthcare Banking 40

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.

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Hadoop Project Big Data Healthcare 52

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. Structured data usually consists of only text.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

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.

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Hadoop Big Data Metadata Java 40