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.

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Hadoop Big Data NoSQL Unstructured Data 52

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

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

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

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

Monte Carlo

OCTOBER 31, 2024

Key Differences Between AI Data Engineers and Traditional Data Engineers While traditional data engineers and AI data engineers have similar responsibilities, they ultimately differ in where they focus their efforts. Challenges Faced by AI Data Engineers Just because “AI” involved doesn’t mean all the challenges go away!

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Data Engineer Data Engineering Engineering Unstructured Data 52

Precisely

MARCH 9, 2023

We will also address some of the key distinctions between platforms like Hadoop and Snowflake, which have emerged as valuable tools in the quest to process and analyze ever larger volumes of structured, semi-structured, and unstructured data. The post Data Warehouse vs. Data Lake appeared first on Precisely.

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Data Lake Data Warehouse Hadoop Raw Data 59

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. The data lakes store data from a wide variety of sources, including IoT devices, real-time social media streams, user data, and web application transactions.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 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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Data Pipeline Designing Data Lake Data Warehouse 98

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

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IT Unstructured Data Data Architecture Government 110

Knowledge Hut

AUGUST 16, 2024

Some companies have started to switch to Hadoop-as-a-Service (HaaS), another terminology for Hadoop on the cloud so Data Scientists need not know the in-depth working of Hadoop. Apache Spark Apache Spark is a Big Data computation framework like Hadoop, and is very popular in the Data Science world.

Data Science 52

Data Science Hadoop Unstructured Data Programming Language 52

ProjectPro

JULY 13, 2015

Large commercial banks like JPMorgan have millions of customers but can now operate effectively-thanks to big data analytics leveraged on increasing number of unstructured and structured data sets using the open source framework - Hadoop. JP Morgan has massive amounts of data on what its customers spend and earn.

Hadoop 52

Hadoop Big Data Data Analytics Banking 52

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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Knowledge Hut

APRIL 23, 2024

Data Usage It stores the data in a sorted manner for future use. It uses data from the past and present to make decisions related to future growth. Data Type Data science deals with both structured and unstructured data. Business Intelligence only deals with structured data.

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Business Intelligence Data Science BI Unstructured Data 52

Knowledge Hut

NOVEMBER 3, 2023

MongoDB is a NoSQL database that’s been making rounds in the data science community. MongoDB’s unique architecture and features have secured it a place uniquely in data scientists’ toolboxes globally. Let us see where MongoDB for Data Science can help you.

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MongoDB Data Science NoSQL ETL Tools 52

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.

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Data Collection Machine Learning Unstructured Data Non-relational Database 52

RandomTrees

SEPTEMBER 17, 2024

In the realm of big data and AI, managing and securing data assets efficiently is crucial. Databricks addresses this challenge with Unity Catalog, a comprehensive governance solution designed to streamline and secure data management across Databricks workspaces. Advantages of the Unity Catalog 1.

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Data Governance Government Metadata Machine Learning 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.

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NoSQL Big Data SQL Database-centric 49

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 replaced its traditional BI structure by integrating big data and Hadoop."-April So what is BI?

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Business Intelligence Big Data BI Hadoop 40

Knowledge Hut

DECEMBER 26, 2023

Using Big Data, they provide technical solutions and insights that can help achieve business goals. They transform data into easily understandable insights using predictive, prescriptive, and descriptive analysis. They are also responsible for improving the performance of data pipelines.

Data Science 97

Data Science BI Business Intelligence Machine Learning 97

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

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Systems Hadoop Metadata Telecommunication 85

Striim

OCTOBER 11, 2024

Additionally, legacy systems frequently struggle with diverse data types, such as structured, semi-structured, and unstructured data. Contemporary pipelines simplify data management by supporting a wide array of data formats and automating many processes.

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Data Pipeline MongoDB Unstructured Data Data Lake 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

Cloudera

OCTOBER 28, 2021

The German underwriters analyzed historical data such as weather, location, breed, type of crop, and a farmer’s experience to assess risk, underwrite and set price exposures. In this way, the Commercial Lines segment of insurance has really been a user of big data since its inception. Another example is fleet management.

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Insurance Transportation Unstructured Data Manufacturing 96

ProjectPro

JANUARY 27, 2023

However, the vast volume of data will overwhelm you if you start looking at historical trends. The time-consuming method of data collection and transformation can be eliminated using ETL. You can analyze and optimize your investment strategy using high-quality structured data.

BI 52

BI ETL Tools Retail Healthcare 52

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Big Query Google’s cloud data warehouse. Database A collection of structured data.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

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Data Lake Data Warehouse Unstructured Data Raw 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. It separates the hidden links and patterns in the data.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

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.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

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?

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Data Pipeline Architecture Kafka AWS 52

ProjectPro

FEBRUARY 16, 2023

Focus Historical data analysis, reporting, and visualization. Input Data Structured data from various sources, such as databases, spreadsheets, and ERP systems. Structured, semi-structured, and unstructured data from multiple sources, such as social media, IoT devices, and sensors.

Business Intelligence 52

Business Intelligence BI Data Mining Algorithm 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.

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Hadoop Big Data Tools Java Big Data 52

Knowledge Hut

NOVEMBER 28, 2023

People use programming mathematics, statistics, and other domain knowledge in data science to extract important insights from big data. In 2023 Data Science has become one of the most sought-after fields for recruiters in India. That is why Data Science is a valued field in the IT and Business sectors.

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Data Science Telecommunication Recruitment Finance 52

ProjectPro

JULY 27, 2021

In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry. that leverage big data analytics and tools. Preparing for data engineer interviews makes even the bravest of us anxious.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

Knowledge Hut

NOVEMBER 17, 2023

Data scientists widely adopt these tools due to their immense benefits. Data Storage Data scientists can use Amazon Redshift. It allows you to execute complex queries on structured and unstructured data. With AWS Glue, you can create a unified catalog within the data lake for faster access.

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