best data science tools for data scientist
DESCRIPTION
Data Science is the analytical field that vitally depends upon the large amount of data, such as Big Data, to analyze the business problem and provide the accurate solution for the problem. But handling the huge amount of data is not the easy task. To avoid manual errors, the automatic computational and logical processes are enhanced via tools and Software. Using that Software and tools, the problem can be solved with a minimum amount of time with high accuracy. [1] 🌐: https://www.tutorsindia.com/ 📧: [email protected] 💬(WA): +91-8754446690 🇬🇧(UK): +44-1143520021TRANSCRIPT
SOFTWARE & TOOLSFOR DATA SCIENCE
An Academic presentation by Dr. Nancy Agnes, Head, Technical Operations, Tutors India Group www.tutorsindia.comEmail: [email protected]
Introduction
Need For Software And Tools
Efficiency Of Software And Tools
Recent Tools And Software In Data Science
Future Scope
Summary
OUTLINE
Today's Discussion
Data Science is the analytical field that vitally depends upon the largeamount of data, such as Big Data, to analyze the business problem andprovide the accurate solution for the problem.
But handling the huge amount of data is not the easy task. To avoidmanual errors, the automatic computational and logical processes areenhanced via tools and Software.
Using that Software and tools, the problem can be solved with a minimumamount of time with high accuracy.
INTRODUCTION
The organization may possess a huge amount of business revenue annually, the vastamount of turnovers and losses, employee strength according to productivity, tounderstand the current market values and strategies can be estimated to forecast theorganization strength.
For instance, the Netflix viewers may increase/decrease according to the consecutiveshows cast in a certain period.
Many of the viewers may withdraw their accounts due to the poor quality of thestreaming. Netflix analyzes the root cause for their withdrawals
NEED FOR SOFTWAREAND TOOLS
The analytics process will be done to predict the cause for thewithdrawal
Based on the analytics report, further modifications and otherrecommendations will be published and cast.
.
By using Software and tools, the accuracy of results for a large number of businessdatasets can be obtained efficiently.
Tools and Software also help transform the data into a visualized format existing in thestructured or semi-structured form of data.
Every Software and tools have a unique way of representing the data in the graphicalformat.
EFFICIENCY OFSOFTWARE AND TOOLS
The Software and tools generate the exact results and outcomes based on the reportimported into it.
The purpose of the data science tools and Software is to extract, manipulate, andprocess the data.
On the other hand, converting the structured data doesn't convey any informationand convert those data into useful information.
Several tools and Software with high flexibility and features with goodextracting and visualizing effects provide more accuracy even whenthe data is large.
Many of the tools and Software provides high-efficiency and accurateresults.
Tableau is the complete data visualization tool. 1.TABLEAU
RECENT TOOLS ANDSOFTWARE IN DATA SCIENCE
It supports all kinds of worksheets and structured form of data for data processing,exploratory data analysis, and database compatibility.
It is not an open-source platform. It is dependent upon the organization necessity. Thevisualization format is very admiring and good looking.
Jupyter Notebook is a peak in the data science market because of its compatibility inboth the statistical analytical languages Python and R.
Jupyter supports coding flexibility Python and R language.
Basically, it is a web-based application which supports all kind of worksheets andspreadsheets for data extraction and data manipulation.
2.JUPYTER NOTEBOOK
Matplotlib developed especially for Python language to provide more plotting andvisualization features.
Matplotlib provides more modules, especially for visualization. For instance, Pyplotprovides more modules for graphs and plots.
4.PYTHONIn recent years, many data scientists plant their roots in the Python language, whichprovide more flexible packages for statistical and mathematical analyses.
Python has the feature to connect the other similar tools like Scipy, Dask, HPAT, Cythonto provide more flexibility and reliability.
3.MATPLOTLIB
As same as Python, R Studio designed especially for statistical andmathematical analytics.
R Studio is the open-source platform.
The console port of the R Studio supports more library packages andanalytical functions.
5.R AND R STUDIO
6.BIGML BigML is completely based on machine learning algorithm for data science and dataanalytics.
It provides more flexible packages with automation regression, linear regressionanalysis, cluster analysis, anomaly detection, and forecasting of time series data.
The BigML has the feature of online assessment from the source website –bigml.com.
FUTURE SCOPE
As the data generating everywhere around the world, handling and manipulating thelarge volume of data will be the tedious process.
So the need for data scientists is vast, and the processing of large amounts of datausing automation tools provides better results.
The errors in manual computations will lead to recomputation which is timeconsumption process.
To ignore those manual errors, tools and Software with high efficiency and accurateresults even for forecasting and predictive analysis.
The minimal time of the process is enough for the Software and tools comparativelymanual computations even for a small number of datasets.
The automation tools exactly predict and provide the outcome based on the traineddata set.
The world is full of data everywhere, and those data can be stored eitherphysically or virtually.
But handling the entire data is not the single-day process.
It a routine for the data scientists to compute the tedious data and produce theoutput for the data.
The dataset can be efficiently manipulated through recent technology-basedtools such as Artificial Intelligence, Machine Learning, Cloud computingalgorithms.
SUMMARY
What's Next in Tech Workspace
Increased task automation and use of artificial intelligence.01
Extra focus on high-value tasks.02
Continuous investment in cybersecurity and security technology.03
A better conscious focus on mental health.04
Greater geographic distribution and representation of the workforce. 05
Technology is bestwhen it brings people together.
MATT MULLENWEG
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