Knowledge Hut

DECEMBER 26, 2023

Of course, handling such huge amounts of data and using them to extract data-driven insights for any business is not an easy task; and this is where Data Science comes into the picture. Mathematical concepts like Statistics and Probability, Calculus, and Linear Algebra are vital in pursuing a career in Data Science.

Data Science 97

Data Science BI Business Intelligence Machine Learning 97

Knowledge Hut

JANUARY 18, 2024

This can sometimes cause confusion regarding their applications in real-world problems and for learning purposes. The key connection between Data Science and AI is data. Some may argue that AI and Machine Learning fall within the broader category of Data Science , but it's essential to recognize the subtle differences.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

Knowledge Hut

APRIL 23, 2024

Big Data vs Small Data: Function Variety Big Data encompasses diverse data types, including structured, unstructured, and semi-structured data. It involves handling data from various sources such as text documents, images, videos, social media posts, and more.

Big Data 52

Big Data Datasets Data Analysis Media 52

U-Next

MARCH 1, 2023

The data engineering process involves the creation of systems that enable the collection and utilization of data. Analyzing this data often involves Machine Learning, a part of Data Science. What is a data warehouse? How does a data warehouse differ from a database? What is AWS Kinesis?

Data Engineer 75

Data Engineer Data Engineering Non-relational Database Engineering 75

Data Engineering Podcast

JULY 1, 2018

Summary Data is often messy or incomplete, requiring human intervention to make sense of it before being usable as input to machine learning projects. What are the limitations of crowd-sourced data labels? When doing data collection from various sources, how do you ensure that intellectual property rights are respected?

Metadata 100

Metadata Machine Learning Data Preparation Data Collection 100

Knowledge Hut

JUNE 28, 2023

Focus Exploration and discovery of hidden patterns and trends in data. Reporting, querying, and analyzing structured data to generate actionable insights. Data Sources Diverse and vast data sources, including structured, unstructured, and semi-structured data.

Data Mining 52

Data Mining Business Intelligence BI Structured Data 52

Knowledge Hut

JANUARY 19, 2024

Acknowledging the escalating demand for data scientists, institutions globally are intensifying efforts to provide comprehensive training aligned with the Data Science Course Syllabus. Exploring data science, I focus on key topics like statistical analysis, machine learning, data visualization, and programming in my course syllabus.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Knowledge Hut

DECEMBER 29, 2023

Professionals from a variety of disciplines use data in their day-to-day operations and feel the need to understand cutting-edge technology to get maximum insights from the data, therefore contributing to the growth of the organization. Engineering and problem-solving abilities based on Big Data solutions may also be taught.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

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

Striim

OCTOBER 11, 2024

A data pipeline refers to a series of processes that transport data from one or more sources to a destination, such as a data warehouse, database, or application. Throughout the pipeline, data undergoes various transformations such as filtering, cleaning, aggregating, enriching, and even real-time analysis.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Cloudera

SEPTEMBER 29, 2021

Among the use cases for the government organizations that we are working on is one which leverages machine learning to detect fraud in payment systems nationwide. Through processing vast amounts of structured and semi-structured data, AI and machine learning enabled effective fraud prevention in real-time on a national scale. .

Medical 83

Medical Government Hospitality Electronics 83

Knowledge Hut

JANUARY 30, 2024

Whether it's aggregating customer interactions, analyzing historical sales trends, or processing real-time sensor data, data extraction initiates the process. Goal To extract and transform data from its raw form into a structured format for analysis. Primary Focus Structuring and preparing data for further analysis.

ETL Tools 52

ETL Tools Database-centric Data Mining Raw Data 52

U-Next

AUGUST 8, 2022

The world demand for Data Science professions is rapidly expanding. Data Science is quickly becoming the most significant field in Computer Science. It is due increasing use of advanced Data Science tools for trend forecasting, data collecting, performance analysis, and revenue maximisation. data structure theory.

Data Science 40

Data Science Coding Programming Language Scala 40

Knowledge Hut

APRIL 25, 2024

Big data can be summed up as a sizable data collection comprising a variety of informational sets. It is a vast and intricate data set. Big data has been a concept for some time, but it has only just begun to change the corporate sector. Join us now and become a data wizard!

Big Data 97

Big Data Entertainment Transportation Banking 97

Monte Carlo

FEBRUARY 15, 2023

What is a data warehouse? A data warehouse is an online analytical processing system that stores vast amounts of data collected within a company’s ecosystem and acts as a single source of truth to enable downstream data consumers to perform business intelligence tasks, machine learning modeling, and more.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

ProjectPro

DECEMBER 17, 2021

Data science and artificial intelligence might be the buzzwords of recent times, but they are of no value without the right data backing them. The process of data collection has increased exponentially over the last few years. Table of Contents Why SQL for Data Science? What is SQL?

Data Science 52

Data Science SQL NoSQL Programming Language 52

Data Engineering Weekly

NOVEMBER 20, 2022

Google AI: The Data Cards Playbook: A Toolkit for Transparency in Dataset Documentation Google published Data Cards , a dataset documentation framework aimed at increasing transparency across dataset lifecycles.

Data Engineer 52

Data Engineer Data Engineering Engineering Datasets 52

Knowledge Hut

NOVEMBER 28, 2023

But before we talk about the salary of a data scientist in India, we have to talk about what Data Science is and why it is so important in the current business sector. As we already said before, Data Science is a field where different methods are used to extract important insights from batches of data.

Data Science 52

Data Science Telecommunication Recruitment Finance 52

ProjectPro

JANUARY 25, 2022

One of the most in-demand technical skills these days is analyzing large data sets, and Apache Spark and Python are two of the most widely used technologies to do this. Python is one of the most extensively used programming languages for Data Analysis, Machine Learning , and data science tasks.

Big Data 52

Big Data Data Process Process Kafka 52

AltexSoft

JUNE 7, 2021

The keyword here is distributed since the data quantities in question are too large to be accommodated and analyzed by a single computer. 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. Processing options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

MARCH 27, 2024

Data can be structured, semi-structured, or unstructured, and users can change the data according to their requirements. Distributing data across multiple data centers is easy with replication. Qubole provides end-to-end services in moving data pipelines with reduced time and effort.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

ProjectPro

OCTOBER 20, 2021

With so many pseudo-data scientists cropping up due to numerous data science bootcamps and courses that offer theoretical learning, the interview questions for AI and machine learning jobs are getting streamlined to filter those who understand how real-world implementation works.

Machine Learning 52

Machine Learning Algorithm Data Science Government 52

ProjectPro

DECEMBER 28, 2021

For example, a pervasive trend identified by IBM's Global Technology Outlook 2015 is that 60% of valuable sensory data can be squandered within milliseconds if not acted! Models can be trained offline using MLlib (Spark's machine learning library) and then used online for streaming data scoring using Spark Streaming.

Architecture 52

Architecture Kafka Java Scala 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

AltexSoft

SEPTEMBER 23, 2021

Data lakes are typically intended for data exploration and machine learning purposes. This means a user has to decide what queries and scripts can be suitable to work with data. The result of experimentation supplies downstream applications with prepared data. Data hub architecture.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

AltexSoft

MAY 14, 2021

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. billion data points. The Ginger.io

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Variety Hadoop stores structured, semi-structured and unstructured data.

Big Data 52

Big Data Hadoop Relational Database AWS 52

U-Next

OCTOBER 25, 2022

What Is Data Manipulation? . In data manipulation, data is organized in a way that makes it easier to read, or that makes it more visually appealing, or that makes it more structured. Data collections can be organized alphabetically to make them easier to understand. .

Business Intelligence 40

Business Intelligence Raw Data Data Cleanse Data Analysis 40

ProjectPro

JULY 27, 2021

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

Snowflake

JANUARY 18, 2023

The function uses Java streaming methods to handle the rows and specialized column formatting defined by the VCF specification—converting the zipped VCF files into an easy-to-query structured and semi-structured data representation inside Snowflake.

Pharmaceutical 84

Pharmaceutical AWS Java Healthcare 84

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. Machine Learning web service to host forecasting code.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

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

Knowledge Hut

DECEMBER 26, 2023

However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured. This mainly happened because data that is collected in recent times is vast and the source of collection of such data is varied, for example, data collected from text files, financial documents, multimedia data, sensors, etc.

Data Engineer 98

Data Engineer Data Engineering Engineering Pipeline-centric 98

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. A site like Twitter has 330 million users , while Facebook has 2.8

Big Data 52

Big Data Coding Project Hadoop 52

U-Next

SEPTEMBER 21, 2022

Not all of this data is erroneous. The majority of this unstructured, meaningless data can be well converted into a more organized (tabular/more comprehensible) format. In simpler terms, good data use implies thriving businesses. . Data mining is a broad and complex process with several components. . Functionality .

Data Mining 40

Data Mining Data Warehouse Business Intelligence Retail 40

U-Next

AUGUST 11, 2022

Data Science is an interdisciplinary field that blends programming skills, domain knowledge, reasoning skills, mathematical and statistical skills to generate value from a large pool of data. Skill requirements for Data Science. Knowing algorithms, mathematics, statistics, and machine learning are essential.

Data Science 40

Data Science Data Cleanse Unstructured Data Machine Learning 40

ProjectPro

NOVEMBER 22, 2021

You'll need to transfer the data back to Pandas DataFrame after processing it in PySpark so that you can use it in Machine Learning apps or other Python programs. Additional libraries on top of Spark Core enable a variety of SQL, streaming, and machine learning applications. Discuss PySpark SQL in detail.

Hadoop 52

Hadoop Python Datasets Metadata 52