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. Considering this information database model is fitted with data.

Data Science 98

Data Science Datasets Database Design Machine Learning 98

ProjectPro

JANUARY 25, 2022

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency. Why use PySpark? To set the master URL, use setMaster(value).

Big Data 52

Big Data Data Process Process Kafka 52

Knowledge Hut

MARCH 27, 2024

An ordered set of data kept in a computer system and typically managed by a database management system (DBMS) is called a database. Table modeling of the data in standard databases facilitates efficient searching and processing. A vital component of our lives is the database. What is a Data Structure?

Database 52

Database Algorithm Relational Database PostgreSQL 52

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. To provide meaningful business insights, it collects and manages data from a variety of sources. In other words, it is the process of converting data into information. .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Grouparoo

DECEMBER 26, 2021

For data storage, the database is one of the fundamental building blocks. They provide a method for storing information in an organized manner that ensures it remains accessible while providing the mechanisms to protect the integrity, confidentiality, and availability of the information they hold.

Database 52

Database NoSQL Relational Database Data Storage 52

Knowledge Hut

DECEMBER 21, 2023

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. To establish a career in big data, you need to be knowledgeable about some concepts, Hadoop being one of them. What is Hadoop?

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 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. Obviously, Big Data processing involves hundreds of computing units. scalability.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Data Engineering Weekly

DECEMBER 18, 2022

Given the characteristic, are we having a “Big Data” problem? Can we spin off a machine with all the data stack and run through the analysis? The author writes an exciting blog, Modern data stack in a Box!! link] Sponsored: Upsolver - Write a SQL Query, Get a Data-in-Motion Pipeline!

Data Engineering 52

Data Engineering Data Engineer Engineering Relational Database 52

Edureka

AUGUST 2, 2023

The ease with which data analysis workflows may be documented and shared thanks to its seamless integration with other well-liked data science tools, such as Jupyter Notebooks.Python’s adaptability goes beyond just data analysis and manipulation, too. Data scientists use SQL to query, update, and manipulate data.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

Knowledge Hut

JANUARY 30, 2024

Whether you're a seasoned data scientist or just stepping into the world of data, come with me as we unravel the secrets of data extraction and learn how it empowers us to unleash the full potential of data. What is data extraction? Primary Focus Structuring and preparing data for further analysis.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

AltexSoft

JUNE 26, 2023

Data collection as the first step in the decision-making process, driven by machine learning. In machine learning projects, data collection precedes such stages as data cleaning and preprocessing, model training and testing, and making decisions based on a model’s output. Data engineering explained in 14 minutes.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 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. doc,docx), PDF files (.pdf),

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Monte Carlo

FEBRUARY 27, 2024

Right now, RAG is the essential technique to make GenAI models useful by giving an LLM access to an integrated, dynamic dataset while responding to prompts. These databases are not just a trend, but a fundamental shift in how data is managed, accessed, and utilized in real-time AI applications.

Data Engineering 59

Data Engineering Data Engineer Engineering High Quality Data 59

ProjectPro

JANUARY 27, 2023

It is extremely important for businesses to process data correctly since the volume and complexity of raw data are rapidly growing. Over the past few years, data-driven enterprises have succeeded with the Extract Transform Load (ETL) process to promote seamless enterprise data exchange.

BI 52

BI ETL Tools Retail Healthcare 52

AltexSoft

AUGUST 29, 2023

Another distinction is the ETL vs. ELT choice: In data warehouses, Extract and Transform processes usually occur before data is loaded into the warehouse. Many organizations also deploy data marts , which are dedicated storage repositories for specific business lines or workgroups. Structured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Rockset

DECEMBER 31, 2022

Introduction Web-based applications face scaling due to the growth of users along with the increasing complexity of data traffic. Along with the complexity of modern business comes the need to process data faster and more robustly. Because of this, standard transactional databases aren’t always the best fit.

Non-relational Database 52

Non-relational Database Healthcare Amazon Web Services NoSQL 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

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. It is often used as a foundation for enterprise data lakes.

Data Lake 57

Data Lake Data Warehouse Hadoop Raw Data 57

ProjectPro

JANUARY 31, 2023

Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Towards Data Science

MARCH 5, 2024

The storage system is using Capacitor, a proprietary columnar storage format by Google for semi-structured data and the file system underneath is Colossus, the distributed file system by Google. In that case, queries are still processed using the BigQuery compute infrastructure but read data from GCS instead.

Bytes 70

Bytes Google Cloud Cloud Storage Utilities 70

Edureka

FEBRUARY 7, 2023

If you want to become a data engineer, you should prepare for the interview process. To help you get a head start on your preparation, I’ve compiled a list of the Top 30+ Azure Data Engineer Interview Questions. It is intended to process enormous amounts of data, including tables with hundreds of millions of rows.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 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. Key Factors to Consider- When choosing an AWS instance type, several key factors should guide your decision-making process.

AWS 52

AWS NoSQL Deep Learning Datasets 52

Data Engineering Weekly

MARCH 24, 2023

Why should we care about Data Creation Process? All Successful Data-Driven organizations have one thing in common; They have a high-quality & efficient data creation process. Data creation is often the differentiator between the success & the failure of a data team.

Engineering 67

Engineering Data Transportation Database 67

AltexSoft

MAY 14, 2021

Not only does Big Data apply to the huge volumes of continuously growing data that come in different formats, but it also refers to the range of processes, tools, and approaches used to gain insights from that data. Key Big Data characteristics. Velocity is the speed at which the data is generated and processed.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

AltexSoft

AUGUST 4, 2021

Some sweets are presented on your display cases for quick access while the rest is kept in the storeroom. Now let’s think of sweets as the data required for your company’s daily operations. Initially, DWs dealt with structured data presented in tabular forms. Moreover, not all organizations use data lakes.

Data Lake 64

Data Lake Data Warehouse ETL Tools Telecommunication 64

Knowledge Hut

DECEMBER 28, 2023

It is a flexible language that can be applied to various projects, such as web development, scientific computing, and data analysis. SQL SQL, or Structured Query Language, is one of the top 5 web development languages used for managing and manipulating relational databases.

Programming Language 52

Programming Language Java Python SQL 52

AltexSoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Data warehouse. Traditional data warehouse platform architecture. Key features of a data lakehouse.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

SEPTEMBER 23, 2021

It’s not a single technology, but rather an architectural approach that unites storages, data integration and orchestration tools. With a data hub, businesses receive the means to structure, and harmonize information collected from various sources. In a nutshell, a model is a specific data structure a database can ingest.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Silectis

JANUARY 3, 2021

If you’re new to data engineering or are a practitioner of a related field, such as data science, or business intelligence, we thought it might be helpful to have a handy list of commonly used terms available for you to get up to speed. Big Data Large volumes of structured or unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

DECEMBER 26, 2023

Big Data is an immense amount of data that is constantly growing exponentially. Due to its vastness and complexity, no traditional data management system can adequately store or process this data. The New York Stock Exchange, which generates one terabyte of new trade data each day, is a classic example of big data.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

U-Next

SEPTEMBER 29, 2022

What Is a Data-Driven Culture? . Data on a daily basis surround us. As data becomes more accessible, companies are leveraging it to grow and make an impact. The importance of data today cannot be overstated. Having a data-driven culture is essential for organizations’ survival and growth. .

Management 52

Management Unstructured Data Data Government 52

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two.

Architecture 52

Architecture Data Lake Medical Datasets 52

Knowledge Hut

OCTOBER 30, 2023

Data Validation: Help validate data against predefined business rules and ensure data quality. Documentation: Maintain documentation for reports, data sources, and data transformation processes. Manage data integration tasks, including data source connections and data transformation processes.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse. In this role, they would help the Analytics team become ready to leverage both structured and unstructured data in their model creation processes. They construct pipelines to collect and transform data from many sources.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Edureka

FEBRUARY 9, 2023

Azure Data Engineers Jobs – The Demand Azure Data Engineer Skills What does an Azure Data Engineer Do? Who is an Azure Data Engineer? Data is an organization’s most valuable asset, so making sure it can be accessed quickly and securely should be a top priority.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52