AltexSoft

JUNE 21, 2023

For machine learning models to predict ADR effectively, a comprehensive understanding of these variables is required in the data preparation stage. Recognizing which factors to consider and which to exclude is a critical step in the data preparation process. Data shortage and poor quality.

Hospitality 52

Hospitality Management Machine Learning Datasets 52

AltexSoft

MAY 5, 2023

Additionally, through predictive analytics and smart home technology , AI can identify potential maintenance issues before they become critical, allowing property managers to address them proactively. So as far as the penetration of AI technologies into revenue management goes, a significant shift is happening.

Machine Learning 59

Machine Learning Hospitality Algorithm Deep Learning 59

ProjectPro

JANUARY 19, 2022

Azure Data Engineers Jobs - The Demand Azure Data Engineer Salary Azure Data Engineer Skills What does an Azure Data Engineer Do? Data is an organization's most valuable asset, so ensuring it can be accessed quickly and securely should be a primary concern. This is where the Azure Data Engineer enters the picture.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

JULY 17, 2021

The job of an AI Engineer comes with many responsibilities, including data preparation , AI programming, algorithm design, data analytics, and a lot more. Once data preparation is complete, constructing Machine Learning-based models is an equally significant part of the job role.

Engineering 40

Engineering Machine Learning Data Science Algorithm 40

AltexSoft

DECEMBER 15, 2021

Namely, AutoML takes care of routine operations within data preparation, feature extraction, model optimization during the training process, and model selection. In the meantime, we’ll focus on AutoML which drives a considerable part of the MLOps cycle, from data preparation to model validation and getting it ready for deployment.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59

ProjectPro

JANUARY 31, 2023

The Big data market was worth USD 162.6 Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. DataNodes store data blocks, whereas NameNodes store these data blocks.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

SEPTEMBER 26, 2021

Big Data refers to the massive volumes of data which is no longer possible to manage using traditional software applications. Automated tools are developed as part of the Big Data technology to handle the massive volumes of varied data sets. Data Scientists use ML algorithms to make predictions on the data sets.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

AltexSoft

MAY 14, 2021

The concept of Big Data isn’t new: It has been the desired fruit for several decades already as the capabilities of software and hardware have made it possible for companies to successfully manage vast amounts of complex data. The process of identifying the sources and then getting Big Data varies from company to company.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Knowledge Hut

DECEMBER 26, 2023

Key Highlights and Benefits The Certification of Professional Achievement in Data Sciences from Columbia University offers comprehensive training, industry recognition, career advancement opportunities, networking prospects, and practical application of data science techniques.

Certification 52

Certification Data Analytics BI AWS 52

ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. How do you Create a Good Big Data Project?

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

SEPTEMBER 6, 2021

Cloud Technology has risen in the latter half of the past decade. Amazon and Google are the big bulls in cloud technology, and the battle between AWS and GCP has been raging on for a while. The Google trends graph above shows how the two technologies have increased over the years, with AWS maintaining a significant margin over GCP.

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

ProjectPro

JANUARY 31, 2022

Traditional data preparation platforms, including Apache Spark, are unnecessarily complex and inefficient, resulting in fragile and costly data pipelines. By doing so, Snowflake has overcome one of the most significant constraints associated with traditional database technology.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

NOVEMBER 15, 2021

Contributing to an open-source big data project has numerous potential benefits for developers and data scientists, including acquiring new skills, interacting with the community, developing a solid network, and sharpening skillset. In addition to analytics and data science, RAPIDS focuses on everyday data preparation tasks.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

JUNE 24, 2021

Data analytics projects for practice help one identify their strengths and weaknesses with various big data tools and technologies. Exploring various big data projects gives a better idea of where your interests lie while working with different analytics tools. to analyze the data.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

ProjectPro

SEPTEMBER 30, 2014

Hadoop’s significance in data warehousing is progressing rapidly as a transitory platform for extract, transform, and load (ETL) processing. Mention about ETL and eyes glaze over Hadoop as a logical platform for data preparation and transformation as it allows them to manage huge volume, variety, and velocity of data flawlessly.

Hadoop 52

Hadoop Unstructured Data ETL Tools ETL System 52

ProjectPro

MAY 18, 2016

Big data industry has made Hadoop as the cornerstone technology for large scale data processing but deploying and maintaining Hadoop clusters is not a cakewalk. The demand for cost effective big data management is driving the growth of HDaaS market. However, they cannot do so as they lack skilled resources.

Hadoop 40

Hadoop Google Cloud Cloud Computing Big Data 40

ProjectPro

JUNE 2, 2015

The General Services Administration has partnered with a Massachusetts based big data analytics company FirstFuel to save $13 million annually in the energy costs across 180 buildings. Business win online when they use hard-to-copy technology to deliver a superior customer experience through mining larger and larger datasets.”-

Big Data 40

Big Data Hadoop Banking Retail 40

ProjectPro

MAY 20, 2015

According to NASSCOM, the global big data analytics market is anticipated to reach $121 billion by 2016. Another research report by IDC predicts 27% compound annual growth rate for big data services and technologies by end of 2017 which equals 6 times the CAGR of the IT market as a whole.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

ProjectPro

AUGUST 11, 2016

When people talk about big data analytics and Hadoop, they think about using technologies like Pig, Hive , and Impala as the core tools for data analysis. R is able to seamlessly integrate with some data processing technologies such as Apache Hadoop and Apache Spark.

Hadoop 40

Hadoop Big Data R (Programming) Programming Language 40

ProjectPro

DECEMBER 10, 2021

It is a data science method that enables computers to predict future actions, results, and trends on the basis of given data. Computers that implement the machine learning technology can operate without any specific hard-core programming. There is one final step in your interview preparation process.

BI 52

BI Cloud Computing SQL Database 52

ProjectPro

DECEMBER 22, 2016

We have collected a library of solved Data Science use-case code examples that you can find here. The various steps involved in the data analysis process include – Data Exploration – Having identified the business problem, a data analyst has to go through the data provided by the client to analyse the root cause of the problem.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52