Knowledge Hut

NOVEMBER 27, 2023

A data scientist’s job needs loads of exploratory data research and analysis on a daily basis with the help of various tools like Python, SQL, R, and Matlab. This role is an amalgamation of art and science that requires a good amount of prototyping, programming and mocking up of data to obtain novel outcomes.

Data Science 52

Data Science Datasets Machine Learning Portfolio 52

AltexSoft

MAY 12, 2022

Particularly, we’ll explain how to obtain audio data, prepare it for analysis, and choose the right ML model to achieve the highest prediction accuracy. But first, let’s go over the basics: What is the audio analysis, and what makes audio data so challenging to deal with. Labeling of audio data in Audacity.

Machine Learning 122

Machine Learning Building Datasets Healthcare 122

Knowledge Hut

JANUARY 29, 2024

This is important before cloud computing will provide the field of data science with the ability to utilize various platforms and tools, to help store and analyze extensive data. Data scientists can use tools such as MS SQL, BusinessObjects, and Microsoft Azure to help them understand cloud computing better.

Cloud Computing 98

Cloud Computing Data Science Cloud Amazon Web Services 98

Knowledge Hut

OCTOBER 30, 2023

Data Visualization: Assist in selecting appropriate visualizations for data presentation and formatting visuals for clarity and aesthetics. Data Analysis: Perform basic data analysis and calculations using DAX functions under the guidance of senior team members.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Knowledge Hut

OCTOBER 27, 2023

Microsoft created Power BI, a business analytics tool that enables users to visualize and analyze data from various sources quickly and interactively. It provides a wide range of features and functionalities, including data preparation, data modeling, data visualization, and collaboration tools.

BI 52

BI Project Datasets Healthcare 52

Knowledge Hut

JUNE 28, 2023

By examining these factors, organizations can make informed decisions on which approach best suits their data analysis and decision-making needs. Parameter Data Mining Business Intelligence (BI) Definition The process of uncovering patterns, relationships, and insights from extensive datasets.

Data Mining 52

Data Mining Business Intelligence BI Datasets 52

Knowledge Hut

DECEMBER 27, 2023

Business analysts have a wide range of responsibilities, including data analysis, report writing, and business process improvement (BPI). Knowledge: The manager must be familiar with business analysis tools, methodologies, and processes for conducting practical data analysis.

Business Analyst 52

Business Analyst Computer Science Finance Data Analysis 52

Knowledge Hut

DECEMBER 7, 2023

In today's data-driven world, businesses and organizations rely heavily on data to make informed decisions and gain a competitive edge. This has increased the demand for professionals skilled in data analysis and visualization tools. Leverage sample datasets and create reports and dashboards using Power BI Desktop.

BI 52

BI Certification Business Intelligence Raw Data 52

Knowledge Hut

JANUARY 30, 2024

In summary, data extraction is a fundamental step in data-driven decision-making and analytics, enabling the exploration and utilization of valuable insights within an organization's data ecosystem. What is the purpose of extracting data? The process of discovering patterns, trends, and insights within large datasets.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Scott Logic

MARCH 25, 2024

There is a preferred workflow to guide a user through the steps of data preparation, analysis and visualisation but this workflow is not mandatory. This really is a platform intentionally designed so that non-technical users can create reports, manipulate data, and perform in-depth data analysis operations.

BI 52

BI Business Intelligence Cloud AWS 52

U-Next

AUGUST 11, 2022

Signal Processing Techniques : These involve changing or manipulating data such that we can see things in it that aren’t visible through direct observation. . Data Analysts: With the growing scope of data and its utility in economics and research, the role of data analysts has risen. is highly beneficial.

Medical 52

Medical Computer Science Scala Machine Learning 52

Knowledge Hut

JUNE 20, 2023

Data Engineer vs Machine Learning Engineer: Responsibilities Data Engineer Responsibilities: Analyze and organize unstructured data Create data systems and pipelines. Analyze trends and patterns Conduct in-depth data analysis, then present the findings. Assemble data for predictive and prescriptive modeling.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

ProjectPro

JANUARY 15, 2021

Undoubtedly, everyone knows that the only best way to learn data science and machine learning is to learn them by doing diverse projects. Table of Contents What is a dataset in machine learning? Why you need machine learning datasets? Where can I find datasets for machine learning? Why you need machine learning datasets?

Datasets 40

Datasets Machine Learning Retail Banking 40

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

Knowledge Hut

JANUARY 25, 2024

What is Data Cleaning? Data cleaning, also known as data cleansing, is the essential process of identifying and rectifying errors, inaccuracies, inconsistencies, and imperfections in a dataset. It involves removing or correcting incorrect, corrupted, improperly formatted, duplicate, or incomplete data.

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

Knowledge Hut

JANUARY 24, 2024

Power BI supports Data Analysis Expression and the M language for data manipulation and modeling. Data Visualization Tableau allows its users to customize dashboards specifically for devices. Tableau also provides flexible data refresh options, enabling me to schedule and manage data updates according to my preferences.

BI 98

BI Business Intelligence Non-relational Database Data Analysis 98

Knowledge Hut

SEPTEMBER 26, 2023

Power BI Basics Microsoft Power BI is a business intelligence and data visualization software that is used to create interactive dashboards and business intelligence reports from various data sources. Dashboards, reports, workspace, datasets, and apps are the building blocks of power BI.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

ProjectPro

FEBRUARY 5, 2021

Nonetheless, it is an exciting and growing field and there can't be a better way to learn the basics of image classification than to classify images in the MNIST dataset. Table of Contents What is the MNIST dataset? Test the Trained Neural Network Visualizing the Test Results Ending Notes What is the MNIST dataset?

Datasets 40

Datasets Deep Learning Medical Algorithm 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. The real-world data is messy. What is Data Cleaning in Data Science?

Data Science 52

Data Science Process Data Cleanse Datasets 52

ProjectPro

JANUARY 24, 2023

Time-saving: SageMaker automates many of the tasks, by creating a pipeline starting from data preparation and ML model training, which saves time and resources. Analyze – Data Wrangler allows you to analyze the features in your dataset at any stage of the data preparation process.

Building 52

Building Algorithm AWS Machine Learning 52

ProjectPro

JUNE 2, 2015

Business win online when they use hard-to-copy technology to deliver a superior customer experience through mining larger and larger datasets.”- It is estimated that a data analyst spends close to 80% of the time in cleaning and preparing the big data for analysis whilst only 20% is actually spent on analysis work.

Big Data 40

Big Data Hadoop Banking Retail 40

ProjectPro

AUGUST 24, 2021

And if you are aspiring to become a data engineer, you must focus on these skills and practice at least one project around each of them to stand out from other candidates. Explore different types of Data Formats: A data engineer works with various dataset formats like.csv,josn,xlx, etc.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

SEPTEMBER 26, 2023

Whether you're running ad-hoc queries or performing complex data transformations, Azure Synapse ensures that your analytics are conducted swiftly, enabling timely decision-making. It supports a variety of query languages, including the industry-standard SQL, as well as popular data analysis languages like Python and R.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

ProjectPro

MAY 20, 2015

It provides the first purpose-built Adaptive Data Preparation Solution(launched in 2013) for data scientist, IT teams, data curators, developers, and business analysts -to integrate, cleanse and enrich raw data into meaningful analytic ready big data that can power operational, predictive , ad-hoc and packaged analytics.

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

Knowledge Hut

DECEMBER 26, 2023

BI encourages using historical data to promote fact-based decision-making instead of assumptions and intuition. Data analysis is carried out by business intelligence platform tools, which also produce reports, summaries, dashboards, maps, graphs, and charts to give users a thorough understanding of the nature of the business.

Business Intelligence 52

Business Intelligence BI Data Mining Data Analysis 52

Knowledge Hut

DECEMBER 7, 2023

Powеr BI empowers organizations with data analysis and visualization capabilities, while DеvOps revolutionizes software development and operations. It transforms data from many sources in order to create dynamic dashboards and Business Intelligence reports. Power BI is among the greatest dashboarding alternatives.

BI 52

BI Business Intelligence Datasets Data Analysis 52

ProjectPro

AUGUST 9, 2021

Top 20 Python Projects for Data Science Without much ado, it’s time for you to get your hands dirty with Python Projects for Data Science and explore various ways of approaching a business problem for data-driven insights. 1) Music Recommendation System on KKBox Dataset Music in today’s time is all around us.

Data Science 52

Data Science Python Project Datasets 52

ProjectPro

AUGUST 30, 2022

Top 5 Loan Prediction Datasets to Practice Loan Prediction Projects Univ.AI Top 5 Loan Prediction Datasets to Practice Loan Prediction Projects Univ.AI A machine learning model can look at this data, which could be static or time-series, and give a probability estimate of whether this loan will be approved.

Machine Learning 52

Machine Learning Coding Project Datasets 52

Knowledge Hut

OCTOBER 11, 2023

Data visuals created by data analysts are used by businesses to make important business decisions and strategies. Whether it’s customer preferences, feedback, or survey results, data is invaluable to the success of a business. As a beginner, you will learn the core concepts of how to turn data into cool reports and charts.

BI 52

BI Business Intelligence Data Analysis Data Preparation 52

ProjectPro

JANUARY 31, 2023

MapReduce is a Hadoop framework used for processing large datasets. Another name for it is a programming model that enables us to process big datasets across computer clusters. This program allows for distributed data storage, simplifying complex processing and vast amounts of data. Explain the data preparation process.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

DECEMBER 22, 2016

Data Analyst Interview Questions and Answers 1) What is the difference between Data Mining and Data Analysis? Data Mining vs Data Analysis Data Mining Data Analysis Data mining usually does not require any hypothesis. Data analysis begins with a question or an assumption.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52

AltexSoft

MAY 5, 2023

Revenue management requires thorough data analysis and evaluation of aspects like booking patterns, occupancy rates, and competition to identify opportunities for revenue enhancement. You can learn more about data preparation for machine learning in our video. The latter is known as dynamic pricing.

Machine Learning 59

Machine Learning Hospitality Algorithm Deep Learning 59

AltexSoft

MAY 14, 2021

As you now know the key characteristics, it gets clear that not all data can be referred to as Big Data. What is Big Data analytics? Big Data analytics is the process of finding patterns, trends, and relationships in massive datasets that can’t be discovered with traditional data management techniques and tools.

Big Data 78

Big Data Data Analytics IT NoSQL 78

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 and Hadoop combined together prove to be an incomparable data crunching tool for some serious big data analytics for business.

Hadoop 40

Hadoop Big Data R (Programming) Programming Language 40

ProjectPro

JUNE 24, 2021

By using the production line dataset, the goal of this data analytics python project is to predict internal failures by making use of data that contains information on tests and measurements obtained for each component. Topic modelling can also be used to classify large datasets of emails.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

U-Next

JUNE 29, 2022

While the ETL workflow is becoming obsolete, it still serves as a common word for the data preparation layers in a big data ecosystem. Working with large amounts of data necessitates more preparation than working with less data. It’s rapid, big, and chaotic. .

Big Data 40

Big Data Big Data Ecosystem Data Lake Raw Data 40

ProjectPro

NOVEMBER 15, 2021

In addition to analytics and data science, RAPIDS focuses on everyday data preparation tasks. Multi-node, multi-GPU deployments are also supported by RAPIDS, allowing for substantially faster processing and training on much bigger datasets. It offers a fault-tolerant storage engine that prioritizes data security.

Big Data 52

Big Data Project Metadata Programming Language 52