Knowledge Hut

JANUARY 30, 2024

This data can be structured, semi-structured, or entirely unstructured, making it a versatile tool for collecting information from various origins. The extracted data is then duplicated or transferred to a designated destination, often a data warehouse optimized for Online Analytical Processing (OLAP).

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

JUNE 20, 2023

Data engineers play three important roles: Generalist: With a key focus, data engineers often serve in small teams to complete end-to-end data collection, intake, and processing. While they might be more experienced than most data engineers, they need a solid understanding of systems design.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Snowflake

MARCH 28, 2023

Top of mind are services that enable fleet management, boost utilization rates, facilitate handshakes with other modes of transport, or match arrival times at warehouses with time slots for offloading. Connected trucks provide data for modular service components that can be customized or sold as needed.

Manufacturing 52

Manufacturing Entertainment Transportation Insurance 52

AltexSoft

FEBRUARY 21, 2023

The algorithm was specifically designed to assist a small family hotel that belongs to Rakuten properties in forecasting ADRs and making informed decisions regarding starting room prices. Data collection and preprocessing As with any machine learning task, it all starts with high-quality data that should be enough for training a model.

Hospitality 52

Hospitality Datasets Algorithm Machine Learning 52

AltexSoft

JUNE 21, 2023

This is where the power of machine learning comes into play, utilizing ADR for hotel price prediction tasks. The initial algorithm was designed to predict ADRs across competitor hotels, furnishing a comparative market perspective. Data shortage and poor quality. Sounds great, right?

Hospitality 52

Hospitality Management Machine Learning Datasets 52

Monte Carlo

MAY 25, 2023

Some of the value companies can generate from data orchestration tools include: Faster time-to-insights. Automated data orchestration removes data bottlenecks by eliminating the need for manual data preparation, enabling analysts to both extract and activate data in real-time. Improved data governance.

Data Pipeline 52

Data Pipeline Data Workflow Data Data Governance 52

U-Next

JUNE 29, 2022

Data must be consumed from many sources, translated and stored, and then processed before being presented understandably. However, the benefits might be game-changing: a well-designed big data pipeline can significantly differentiate a company. Preparing data for analysis is known as extract, transform and load (ETL).

Big Data 40

Big Data Big Data Ecosystem Data Lake Raw Data 40

U-Next

SEPTEMBER 23, 2022

The fast development of digital technologies, IoT goods and connectivity platforms, social networking apps, video, audio, and geolocation services has created the potential for massive amounts of data to be collected/accumulated. Financial services firms use big data platforms for risk management and real-time market data analysis. .

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

Knowledge Hut

FEBRUARY 1, 2024

You cannot expect your analysis to be accurate unless you are sure that the data on which you have performed the analysis is free from any kind of incorrectness. Data cleaning in data science plays a pivotal role in your analysis. It’s a fundamental aspect of the data preparation stages of a machine learning cycle.

Data Science 52

Data Science Process Data Cleanse Datasets 52

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 Processing: This is the final step in deploying a big data model.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

JANUARY 31, 2023

Data Augmentation Techniques How to do Data Augmentation in Keras? How to do Data Augmentation in Tensorflow? How to do Data Augmentation in Caffe? FAQ's What is Data Augmentation in Deep Learning? Data collection and labeling (annotating) can be time-consuming and expensive for deep-learning models.

Deep Learning 52

Deep Learning Datasets Machine Learning Data 52

ProjectPro

MAY 31, 2021

To create a successful data project, collect and integrate data from as many different sources as possible. Here are some options for collecting data that you can utilize: Connect to an existing database that is already public or access your private database.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

FEBRUARY 21, 2023

Due to the enormous amount of data being generated and used in recent years, there is a high demand for data professionals, such as data engineers, who can perform tasks such as data management, data analysis, data preparation, etc.

Certification 52

Certification Data Engineering Data Engineer Engineering 52