Knowledge Hut

MAY 31, 2023

Sales Data Analysis It involves the analysis of data on every aspect of a company’s sales. Excel or Google Sheets can clean and analyze data for charts and graphs. Python or R is good for advanced data analysis and statistical modeling, like looking for trends or making predictions.

Project 52

Project Datasets Media Python 52

Knowledge Hut

MARCH 14, 2024

Data Analysis: Proficiency in data analysis is crucial for a manager to make informed, data-driven decisions. Desired skills include familiarity with tools like R programming, Python, and Business Intelligence ( BI ) software such as Tableau and Power BI.

Management 52

Management Certification Education Portfolio 52

Knowledge Hut

FEBRUARY 11, 2023

Data analysis is a part of the business development and innovation of superior products. Hence, the scope for data analysis is ever-growing. In addition, the data analyst plays a role in identifying potential possibilities for product and business development.

Retail 52

Retail Healthcare Education Data Mining 52

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

Knowledge Hut

FEBRUARY 12, 2023

It has automated systems for data processing, which removes the requirement for manual operations. Data science jobs in USA for freshers salary need to possess this skill to enter the field of data analysis. It involves complex calculations applied to data collected and refined to conclude.

Data Science 52

Data Science Computer Science Portfolio Certification 52

ProjectPro

DECEMBER 14, 2021

Customer Churn Analysis 2. Product Sales Data Analysis 3. Marketing Campaign Insights Analysis 4. Financial Performance Analysis 5. Healthcare Sales Analysis Intermediate-Level Power BI Project Ideas 6. Loan Application Analysis 10. Airport Authority Data Analysis 12.

BI 52

BI Project Business Intelligence Datasets 52

Knowledge Hut

JUNE 30, 2023

Key Benefits and Takeaways: Discover the many data storage and processing methods, including databases, caches, and messaging systems. Investigate the difficulties and solutions in developing distributed systems and ensuring data consistency. Learn about data analysis techniques, data integration, serialization, and data pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

OCTOBER 5, 2023

AWS Big Data specialists should thoroughly understand programming languages such as C and C++, technological applications, and cloud environments. Besides, they should be well-versed in data analysis and statistics. Data structures, data modeling, and programming skills are essential.

Big Data 52

Big Data AWS Certification Amazon Web Services 52

ProjectPro

NOVEMBER 30, 2021

You will learn how to use Exploratory Data Analysis (EDA) tools and implement different machine learning algorithms like Neural Networks, Support Vector Machines, and Random Forest in R programming language. A senior business analyst is often expected to possess knowledge of Big Data tools.

Business Analyst 52

Business Analyst Project Retail Datasets 52

Knowledge Hut

JANUARY 19, 2024

"Python for Data Analysis" Wes McKinney Practical guide to data analysis using Python Beginner/Intermediate Basic Python knowledge Focuses on practical data analysis using Python, covering topics like data cleaning, visualization, and manipulation with pandas, making it an excellent resource for hands-on learning. "The

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

ProjectPro

FEBRUARY 5, 2022

So, how can data analysis tools help us? It will introduce you to the basics of time series and shine a light on various tools used for Exploratory Data Analysis. You will learn how to preprocess the data and plot various graphs using libraries in Python. Many people believe that global warming is a hoax.

Deep Learning 52

Deep Learning Datasets Python Machine Learning 52

Knowledge Hut

FEBRUARY 7, 2023

A data science platform is software that includes a variety of technologies for machine learning, data science, and other advanced analytics projects. Typically, data science projects involve using an abundance of ls (eg. GUI Dashboards They have integrated dashboards to help visualize the graphs and results for the clients.

Data Science 52

Data Science Google Cloud Programming Language AWS 52

Edureka

FEBRUARY 1, 2023

Other topics covered include performance measurement tools like Balanced Scorecard (BSC) and contemporary approaches such as ‘big data analysis. It provides guidance on how these concepts can be applied practically to identify trends in employee performance or turnover rate.

Certification 52

Certification Recruitment Programming R (Programming) 52

ProjectPro

JUNE 17, 2015

According to Dice, there is a significant 11% increase in paychecks for big data jobs associated with MapReduce. Organizations that were earlier dependent on legacy systems for statistical analysis are on the verge of adopting a new open source alternative R.

Cloud Computing 40

Cloud Computing Big Data R (Programming) Big Data Skills 40

ProjectPro

SEPTEMBER 27, 2021

Covariance In Finance and Portfolio Management Correlation vs. Covariance: Machine Learning Project Ideas FAQs Correlation vs. Covariance We will now explore the two statistical concepts often used together to perform exploratory data analysis over a dataset. How to find correlations among feature variables in R?

Datasets 52

Datasets Finance Portfolio Banking 52

ProjectPro

JANUARY 6, 2022

Table of Contents Why Use Python for Data Visualization? Top 10 Python Data Visualization Libraries 1. Pygal Learning Python for Data Analysis and Visualization FAQs Is matplotlib better than plotly? Which library is best for data visualization in Python? Why Use Python for Data Visualization? Matplotlib 2.

Python 52

Python Datasets Programming Language Data Science 52

ProjectPro

NOVEMBER 10, 2016

Professionals with knowledge of SQL can easily mine the data using Hive component of Hadoop because HiveQL is a query language similar to SQL. 4) With increasing demand for data scientist in the big data market, Hadoop developers are still on the verge of adding Python and R programming skills to their skill set.

Hadoop 52

Hadoop NoSQL Java Electronics 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

ProjectPro

SEPTEMBER 26, 2021

Senior Big Data Engineer Salary, The average salary of a Big Data Engineer with over 8 to 10 years of experience is around $120K. The senior-level roles require expert knowledge and skills in complex data analysis and programming. It can go up to $170K annually as per the skill-set and expertise.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

JANUARY 20, 2022

R programming With over 2 million users and 18000+ packages in the CRAN open-source repository, R is an incredible programming language for machine learning. R is a widely-used programming language in machine learning for statistical computing, analysis, and visualization. Is machine learning hard?

Machine Learning 52

Machine Learning Deep Learning Algorithm Programming Language 52

ProjectPro

FEBRUARY 24, 2016

Other Hadoop-related tools that are in demand for data scientists include MapReduce (22%), Pig (16%), and Hive (31%). R is the language of choice for doing data analysis. 32% of the job postings on LinkedIn mention R programming language as a skill requirement for data scientists.

Hadoop 40

Hadoop Data Science Computer Science R (Programming) 40

ProjectPro

AUGUST 21, 2015

IBM has a nice, simple explanation for the four critical features of big data: a) Volume –Scale of data b) Velocity –Analysis of streaming data c) Variety – Different forms of data d) Veracity –Uncertainty of data Here is an explanatory video on the four V’s of Big Data 3.

Hadoop 40

Hadoop Big Data Metadata Java 40