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 Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

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

WeCloudData

OCTOBER 19, 2021

Methodology In order to meet the technical requirements for recommender system development as well as other emerging data needs, the client has built a mature data pipeline through the use of cloud platforms like AWS in order to store user clickstream data, and Databricks in order to process the raw data.

Consulting 52

Consulting Systems NoSQL Raw Data 52

WeCloudData

OCTOBER 19, 2021

Methodology In order to meet the technical requirements for recommender system development as well as other emerging data needs, the client has built a mature data pipeline through the use of cloud platforms like AWS in order to store user clickstream data, and Databricks in order to process the raw data.

Consulting 52

Consulting Systems NoSQL Raw Data 52

Knowledge Hut

JUNE 20, 2023

Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

ProjectPro

JUNE 9, 2021

Data Science- Definition Data Science is an interdisciplinary branch encompassing data engineering and many other fields. Data Science involves applying statistical techniques to raw data, just like data analysts, with the additional goal of building business solutions. Who is a Data Scientist?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Science 52

Knowledge Hut

JANUARY 19, 2024

Machine Learning Unpacking the process of making human language understandable to machines, including topics like regression analysis, Naive Bayes Algorithm, and more. Business Intelligence Transforming raw data into actionable insights for informed business decisions. Implementing machine learning magic.

Data Science 52

Data Science Machine Learning Algorithm Datasets 52

AltexSoft

DECEMBER 21, 2021

When people hear about artificial intelligence, deep learning, and machine learning , many think of movie-like robots that resemble or even outperform human intelligence. Others believe that such machines simply consume information and learn from it by themselves. What is data labeling? How data labeling works.

Machine Learning 52

Machine Learning Process Raw Data Datasets 52

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. They are responsible for changing the design, development, and management of data pipelines while also managing the data sources for effective data collection.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

AltexSoft

MAY 12, 2023

Tools and platforms for unstructured data management Unstructured data collection Unstructured data collection presents unique challenges due to the information’s sheer volume, variety, and complexity. The process requires extracting data from diverse sources, typically via APIs.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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

U-Next

JULY 4, 2022

Therefore the demand for data scientists and other data science professionals is increasing. Anyone who desires to pursue a data scientist career path should have deep knowledge of mathematics, statistics, deep learning, artificial intelligence, machine learning, etc. Why is Data Science Important?

Data Science 40

Data Science Data Architect Data Mining Recruitment 40

ProjectPro

AUGUST 16, 2021

Machine Learning Projects on Classification 2. Machine Learning Projects on Prediction 3. Machine Learning Projects on Computer Vision 4. Machine Learning Projects on Natural Language Processing (NLP) 5. Deep Learning and Neural Network Projects 6.

Machine Learning 40

Machine Learning Coding Project Deep Learning 40

U-Next

AUGUST 18, 2022

Data Science may combine arithmetic, business savvy, technologies, algorithm, and pattern recognition approaches. These factors all work together to help us uncover underlying patterns or observations in raw data that can be extremely useful when making important business choices.

Unstructured Data 40

Unstructured Data Data Science Medical Business Intelligence 40

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. Strong proficiency in using SQL for data sourcing.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

AUGUST 21, 2015

Data that can be stored in traditional database systems in the form of rows and columns, for example, the online purchase transactions can be referred to as Structured Data. Data that can be stored only partially in traditional database systems, for example, data in XML records can be referred to as semi-structured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

Edureka

MARCH 26, 2025

Multiple levels: Raw data is accepted by the input layer. Deep Layers: Discover patterns by extracting features. Hidden Layers : Parameters that can be changed to influence how the network learns are called weights and biases. Receives raw data, with each neuron representing a feature of the input.

Raw Data 40

Raw Data Architecture Deep Learning Finance 40

Knowledge Hut

NOVEMBER 27, 2023

Developing technical skills is essential, starting with foundational knowledge in mathematics, including calculus and linear algebra, which underpin machine learning and deep learning concepts. Common processes are: Collect raw data and store it on a server.

Data Science 52

Data Science Datasets Machine Learning Portfolio 52

ProjectPro

OCTOBER 29, 2021

Since then, many other well-loved terms, such as “data economy,” have come to be widely used by industry experts to describe the influence and importance of big data in today’s society. How then is the data transformed to improve data quality and, consequently, extract its full potential?

Data Mining 52

Data Mining Datasets Machine Learning Metadata 52

U-Next

AUGUST 3, 2022

The people who have inquiries about data are known as Data Scientists. Additionally, they must be able to formulate those questions utilising a variety of tools, including analytic, economic, deep learning, and scientific techniques. What are Data Scientist roles?

Data Science 52

Data Science Retail Computer Science Entertainment 52

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. To build a big data project, you should always adhere to a clearly defined workflow.

Big Data 52

Big Data Coding Project Hadoop 52

Edureka

APRIL 1, 2025

Data augmentation is critical for boosting the performance of machine learning models, particularly deep learning models. The quality, amount, and importance of training data are important for how well these models perform. One of the main problems with using machine learning in real life is not having enough data.

Datasets 40

Datasets Machine Learning Deep Learning Data 40

ProjectPro

NOVEMBER 30, 2021

The crux of all data-driven solutions or business decision-making lies in how well the respective businesses collect, transform, and store data. When working on real-time business problems, data scientists build models using various Machine Learning or Deep Learning algorithms.

Process 52

Process Data Warehouse Data Pipeline AWS 52