Knowledge Hut

MARCH 27, 2024

You can check out the Big Data Certification Online to have an in-depth idea about big data tools and technologies to prepare for a job in the domain. To get your business in the direction you want, you need to choose the right tools for big data analysis based on your business goals, needs, and variety.

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Big Data Data Analytics MongoDB Big Data Tools 52

Knowledge Hut

JULY 26, 2023

Veracity meaning in big data is the degree of accuracy and trustworthiness of data, which plays a pivotal role in deriving meaningful insights and making informed decisions. This blog will delve into the importance of veracity in Big Data, exploring why accuracy matters and how it impacts decision-making processes.

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Big Data Data Cleanse Retail Healthcare 52

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. 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. Which Big Data tasks does Spark solve most effectively? How does it work?

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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.

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Big Data Hadoop Relational Database AWS 52

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). While functional, our current setup for managing tables is fragmented.

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Big Data Data Management Management Metadata 78

Knowledge Hut

DECEMBER 21, 2023

In the present-day world, almost all industries are generating humongous amounts of data, which are highly crucial for the future decisions that an organization has to make. This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 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. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

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Big Data Data Analytics IT NoSQL 78

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. 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.

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Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

NOVEMBER 15, 2021

The adaptability and technical superiority of such open-source big data projects make them stand out for community use. As per the surveyors, Big data (35 percent), Cloud computing (39 percent), operating systems (33 percent), and the Internet of Things (31 percent) are all expected to be impacted by open source shortly.

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Big Data Project Metadata Programming Language 52

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineer is one of the most popular job profiles in the data industry. This blog on Big Data Engineer salary gives you a clear picture of the salary range according to skills, countries, industries, job titles, etc. Big Data gets over 1.2 What does a big data engineer do?

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Big Data Data Engineering Data Engineer Engineering 52

Striim

SEPTEMBER 11, 2024

This is a more efficient data pipeline methodology because it only gets triggered when there is a change to the source.” Striim, for instance, facilitates the seamless integration of real-time streaming data from various sources, ensuring that it is continuously captured and delivered to big data storage targets.

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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. What is Big Data Fabric?

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Big Data NoSQL Hadoop Data Lake 44

Edureka

JULY 4, 2024

Frustrated due to that cumbersome big data? Overwhelmed with log files and sensor data? It is a cloud-based service by Amazon Web Services (AWS) that simplifies processing large, distributed datasets using popular open-source frameworks, including Apache Hadoop and Spark. Amazon EMR is the right solution for it.

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AWS Amazon Web Services Hadoop Big Data 52

Knowledge Hut

MAY 2, 2024

Why We Need Big Data Frameworks Big data is primarily defined by the volume of a data set. Big data sets are generally huge – measuring tens of terabytes – and sometimes crossing the threshold of petabytes. It is surprising to know how much data is generated every minute.

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Hadoop Scala Datasets Java 96

Monte Carlo

MAY 28, 2024

Let’s see what it takes to design an ingestion architecture that ensures reliable, real-time data processing and supports effective decision-making in big data environments. Common Tools Data Sources Identification with Apache NiFi : Automates data flow, handling structured and unstructured data.

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Data Ingestion Architecture Designing Hadoop 52

Knowledge Hut

JUNE 28, 2023

In our data-driven world, our lives are governed by big data. The TV shows we watch, the social media we follow, the news we read, and even the optimized routes we take to work are all influenced by the power of big data analytics. Focus Exploration and discovery of hidden patterns and trends in data.

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Data Mining Business Intelligence BI Structured Data 52

Data Engineering Weekly

AUGUST 4, 2024

It also introduces innovative constrained generation techniques that promise to revolutionize how we approach structured data generation. We look at efficiency in data processing within a single node, which increases the momentum for systems like DuckDB, Arrow, and Polaris.

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Data Engineering Data Engineer Engineering Data 80

ProjectPro

APRIL 27, 2016

Scott Gnau, CTO of Hadoop distribution vendor Hortonworks said - "It doesn't matter who you are — cluster operator, security administrator, data analyst — everyone wants Hadoop and related big data technologies to be straightforward. Sparkling new innovations are easy to find in the big data world.

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Hadoop Big Data Technology Kafka 40

Knowledge Hut

DECEMBER 26, 2023

They identify business problems and opportunities to enhance the practices, processes, and systems within an organization. Using Big Data, they provide technical solutions and insights that can help achieve business goals. They are also responsible for improving the performance of data pipelines.

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Data Science BI Business Intelligence Machine Learning 97

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.

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NoSQL Big Data SQL Database-centric 49

Knowledge Hut

APRIL 25, 2023

The tremendous growth in data generation, then the rise in data engineer jobs - there’s no arguing the fact that the big data industry is at its best pace and you, as an aspiring data engineer, have a lot to learn and make out of it - including some tools!

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Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Monte Carlo

OCTOBER 31, 2024

Both traditional and AI data engineers should be fluent in SQL for managing structured data, but AI data engineers should be proficient in NoSQL databases as well for unstructured data management.

Data Engineering 52

Data Engineering Data Engineer Engineering Unstructured Data 52

Knowledge Hut

DECEMBER 29, 2023

Data scientists may improve their knowledge and response to crucial business demands by opting to specialize in a subfield of their subject. It's possible they'll zero down on a certain data kind, like Big Data, or a computer language. Knowing which data to utilize, how to arrange the data, and so on is essential.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Edureka

AUGUST 2, 2023

It is a crucial tool for data scientists since it enables users to create, retrieve, edit, and delete data from databases.SQL (Structured Query Language) is indispensable when it comes to handling structured data stored in relational databases. Data scientists use SQL to query, update, and manipulate data.

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Programming Language Programming Scala Pharmaceutical 52

Data Engineering Weekly

FEBRUARY 12, 2023

Data Engineering Weekly readers can use the DataWeekly20 promo code to get a 20% discount on the ticket price. Link to Register: [link] Promo Code: DataWeekly20 MotherDuck: Big Data is Dead All large data sets are generated over time. Time is almost always an axis in a data set. New orders come in every day.

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

Striim

OCTOBER 11, 2024

While legacy ETL has a slow transformation step, modern ETL platforms, like Striim, have evolved to replace disk-based processing with in-memory processing. This advancement allows for real-time data transformation , enrichment, and analysis, providing faster and more efficient data processing.

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Data Pipeline MongoDB Unstructured Data Data Lake 52

ProjectPro

MAY 20, 2015

It is difficult to stay up-to-date with the latest developments in IT industry especially in a fast growing area like big data where new big data companies, products and services pop up daily. With the explosion of Big Data, Big data analytics companies are rising above the rest to dominate the market.

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Big Data Hadoop Business Analyst Data Analytics 40

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data is generally not loaded into a data warehouse unless a use case has been defined for the data.

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Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. Table of Contents What is a Data Pipeline? The Importance of a Data Pipeline What is an ETL Data Pipeline? What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Striim

AUGUST 22, 2024

Streams of data are continuously queried with Streaming SQL , enabling correlation, anomaly detection, complex event processing, artificial intelligence/machine learning, and live visualization. Because of this, streaming analytics is especially impactful for fraud detection, log analysis, and sensor data processing use cases.

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Data Warehouse Retail Machine Learning Database 52

ProjectPro

SEPTEMBER 9, 2021

Apache Hive and Apache Spark are the two popular Big Data tools available for complex data processing. To effectively utilize the Big Data tools, it is essential to understand the features and capabilities of the tools. Spark SQL, for instance, enables structured data processing with SQL.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Edureka

JANUARY 18, 2024

This guide provides a comprehensive understanding of the essential skills and knowledge required to become a successful data scientist, covering data manipulation, programming, mathematics, big data, deep learning, and machine learning technologies. Table of Contents Introduction to Data Science What is Data Science?

Data Science 40

Data Science Deep Learning Machine Learning NoSQL 40

Knowledge Hut

NOVEMBER 17, 2023

AWS has changed the life of data scientists by making all the data processing, gathering, and retrieving easy. Analytics Another essential tool being offered by Amazon for a data scientist is- Amazon Athena is a query service for analyzing the data in Amazon S3 or Glacier. It works using standard SQL queries.

AWS 52

AWS Data Science Certification Amazon Web Services 52

Edureka

FEBRUARY 8, 2024

Different instance types offer varying levels of compute power, memory, and storage, which directly influence tasks such as data processing, application responsiveness, and overall system throughput. 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

Edureka

JUNE 1, 2023

Without spending a lot of money on hardware, it is possible to acquire virtual machines and install software to manage data replication, distributed file systems, and entire big data ecosystems. This happens often in data analytics since running reports on huge data processes is done once in a while.

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AWS Data Analytics Cloud Amazon Web Services 52

Edureka

JULY 16, 2024

Introduction Amazon Redshift, a cloud data warehouse service from Amazon Web Services (AWS), will directly query your structured and semi-structured data with SQL. It is also compatible with other AWS services, offering a complete solution for handling, processing, and utilizing data.

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AWS Data Warehouse Amazon Web Services Business Intelligence 40