ProjectPro

JUNE 6, 2025

Million opportunities for remote and on-site data engineering roles. So, have you been wondering what happens to all the data collected from different sources, logs on your machine, data generated from your mobile, data in databases, customer data, and so on? We call this system Data Engineering.

Data Science 40

Data Science Data Engineer Data Engineering Engineering 40

ProjectPro

JUNE 6, 2025

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 40

Big Data Data Process Process Kafka 40

ProjectPro

JUNE 6, 2025

2) Cryptocurrency Analysis AI-powered agents are transforming cryptocurrency analysis by automating data collection, trend detection, and market predictions. The Report Writer then synthesizes insights into a structured report. Source Code: How to Build an LLM-Powered Data Analysis Agent?

Project 59

Project Building Banking Healthcare 59

ProjectPro

JUNE 6, 2025

Step 3: Developing Your Generative AI Solution Once you’ve gathered your training data and selected the appropriate frameworks, it’s time to start developing your generative AI model. This involves: Model Design- Choose the right architecture—GANs for images, VAEs for structured data.

Building 52

Building Banking Deep Learning SQL 52

ProjectPro

JUNE 6, 2025

Role of LLMs for Web Scraping LLMs are adept at handling unstructured data and transforming it into meaningful insights. Using their natural language understanding capabilities, LLMs can: Summarize scraped content, such as distilling product reviews into sentiment analysis.

Project 40

Project Unstructured Data Raw Data Python 40

ProjectPro

JUNE 6, 2025

The data engineer skill of building data warehousing solutions expects a data engineer to curate data and perform data analysis on that data from multiple sources to support the decision-making process. In such instances, raw data is available in the form of JSON documents, key-value pairs, etc.,

Data Engineer 49

Data Engineer Data Engineering Engineering Hadoop 49

ProjectPro

JUNE 6, 2025

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 40

Big Data Hadoop Relational Database AWS 40

Knowledge Hut

FEBRUARY 29, 2024

Get to know more about data science for business. Learning Data Analysis in Excel Data analysis is a process of inspecting, cleaning, transforming and modelling data with an objective of uncover the useful knowledge, results and supporting decision. In data analysis, EDA performs an important role.

Data Science 98

Data Science Database Design Machine Learning Programming Language 98

ProjectPro

JUNE 6, 2025

Become a Job-Ready Data Engineer with Complete Project-Based Data Engineering Course ! Big data is often characterized by the seven V's: Volume , Variety , Velocity, Variability, Veracity, Visualization, and Value of data. Database Management Systems Big Data Engineer works on unstructured and semi-structured data.

Big Data 45

Big Data Big Data Skills Hadoop Scala 45

ProjectPro

JUNE 6, 2025

They provide a centralized repository for data, known as a data warehouse, where information from disparate sources like databases, spreadsheets, and external systems can be integrated. This integration facilitates efficient retrieval and data analysis, enabling organizations to gain valuable insights and make informed decisions.

Data Storage 58

Data Storage PostgreSQL Data Warehouse AWS 58

Striim

SEPTEMBER 11, 2024

Third-Party Data: External data sources that your company does not collect directly but integrates to enhance insights or support decision-making. These data sources serve as the starting point for the pipeline, providing the raw data that will be ingested, processed, and analyzed.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Confluent

JUNE 13, 2019

You might think that data collection in astronomy consists of a lone astronomer pointing a telescope at a single object in a static sky. While that may be true in some cases (I collected the data for my Ph.D. thesis this way), the field of astronomy is rapidly changing into a data-intensive science with real-time needs.

Kafka 102

Kafka Bytes Data Pipeline Transportation 102

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. To make accurate conclusions based on the analysis of the data, you need to understand what that data represents in the first place.

Data Science 97

Data Science BI Data Mining Business Intelligence 97

ProjectPro

JUNE 6, 2025

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

Knowledge Hut

JANUARY 18, 2024

Data Science initiatives from an operational standpoint help organizations optimize various aspects of their business, such as supply chain management , inventory segregation, and management, demand forecasting, etc. A data analyst would be a professional who will be able to accomplish all the tasks mentioned in the process of data analysis.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

Knowledge Hut

APRIL 23, 2024

As organizations strive to gain valuable insights and make informed decisions, two contrasting approaches to data analysis have emerged, Big Data vs Small Data. These contrasting approaches to data analysis are shaping the way organizations extract insights, make predictions, and gain a competitive edge.

Big Data 52

Big Data Media Datasets Data Analysis 52

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. The data can also show that the student succeeds well with online instruction.

Big Data 97

Big Data Entertainment Transportation Banking 97

ProjectPro

JUNE 6, 2025

LlamaIndex Best For - Integrating large language models (LLMs) with structured data sources to create powerful, context-aware AI applications for advanced data querying and analysis. SingleStore introduces a powerful new Notebook feature, designed to streamline complex data analysis , machine learning, and exploration.

Engineering 40

Engineering Machine Learning Coding Architecture 40

AltexSoft

MAY 12, 2023

This article delves into the realm of unstructured data, highlighting its importance, and providing practical guidance on extracting valuable insights from this often-overlooked resource. We will discuss the different data types, storage and management options, and various techniques and tools for unstructured data analysis.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Knowledge Hut

DECEMBER 29, 2023

Learning Outcomes: You will understand the processes and technology necessary to operate large data warehouses. Engineering and problem-solving abilities based on Big Data solutions may also be taught. It separates the hidden links and patterns in the data. Data mining's usefulness varies per sector.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

OCTOBER 24, 2023

Critical Thinking Because they must match the client's expectations with their analysis of the data, business analysts need to be able to think critically. Business analysts must therefore put business requirements and data analysis in order of importance, considering several factors.

Business Analyst 98

Business Analyst Business Intelligence SQL Programming Language 98

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. Data access options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

JUNE 28, 2023

It also entails data utilization, analysis techniques, user roles, and applications, allowing for a comprehensive comparison between business intelligence and data mining cycle. By examining these factors, organizations can make informed decisions on which approach best suits their data analysis and decision-making needs.

Data Mining 52

Data Mining Business Intelligence BI Structured Data 52

Netflix Tech

JULY 21, 2022

Data Analysis and Observations Without diving very deep into the actual devices and results of the classification, we now show some examples of how we could use the structured data for some preliminary analysis and make observations. Acknowledgements I would like to thank the members of various teams?

Machine Learning 78

Machine Learning Datasets Big Data Manufacturing 78

Edureka

AUGUST 2, 2023

Their efforts make ensuring that data is accurate, dependable, and consistent, laying the groundwork for data analysis and decision-making. What does a Data Processing Analysts do ? A data processing analyst’s job description includes a variety of duties that are essential to efficient data management.

Data Process 52

Data Process Process Data Cleanse Data Mining 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. Data analysis.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JUNE 6, 2025

Benefits of Data wrangling Data Wrangling provides several benefits, including: It converts data into a required format suitable for the final system, which typically assists in making well-informed decisions. It significantly enhances data quality by removing unwanted rows and empty cells from the data frame.

Raw Data 58

Raw Data Programming Language Unstructured Data R (Programming) 58

Sync Computing

NOVEMBER 7, 2024

Depending on what sort of leaky analogy you prefer, data can be the new oil , gold , or even electricity. Of course, even the biggest data sets are worthless, and might even be a liability, if they arent organized properly. Data collected from every corner of modern society has transformed the way people live and do business.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 52

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

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

Knowledge Hut

JANUARY 30, 2024

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Output Structured data ready for analysis.

Database-centric 52

Database-centric ETL Tools Data Mining Data Cleanse 52

ProjectPro

JUNE 6, 2025

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. NoSQL databases are designed to store unstructured data like graphs, documents, etc.,

Data Science 40

Data Science SQL NoSQL Programming Language 40

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

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. NoSQL databases are designed to store unstructured data like graphs, documents, etc.,

Data Science 52

Data Science SQL NoSQL Programming Language 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.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Snowflake

JANUARY 18, 2023

Alignment of sequence data with a reference genome and variant-calling algorithms are key elements of primary and secondary genomic data analysis. The next step—tertiary analysis—involves analyzing large and dynamic collections of this preprocessed data, frequently packaged and distributed as compressed VCF files.

Pharmaceutical 98

Pharmaceutical AWS Java Healthcare 98

AltexSoft

JULY 27, 2021

Google singles out four key phases through which a recommender system processes data. They are information collection, storing, analysis, and filtering. Data collection. The initial phase involves gathering relevant data to create a user profile or model for prediction tasks. Data analysis.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76