1. The basic definition of Data, Analytics, and Data Analytics
2. Definition: Data: Data is a set of values of qualitative or quantitative variables. It is information in the raw or unorganized form. It may be a fact, figure, characters, symbols etc
Analytics: Analytics is the discovery, interpretation, and communication of meaningful patterns in data and applying those patterns towards effective decision making.
Data Analytics: Data analytics refers to qualitative and quantitative techniques and processes used to enhance productivity and business gain.
3.Types of analytics: Predictive Analytics (What could happen?)
Prescriptive Analytics (What should we do)
Descriptive Analytics (What has happened?)
4.Why Data analytics? Data Analytics is needed in Business to Consumer applications (B2C)
5.The process of Data analytics: Data requirements,
Data collection, Data processing, Data cleaning, Exploratory data analysis,
Modeling and algorithms, Data product, Communication
6.The scope of Data Analytics: Bright future of data analytics, many professionals and students are interested in a career in data analytics.
7.Importance of data analytics:1. Predict customer trends and behaviors
Analyze,
2 interpret and deliver data in meaningful ways
3.Increase business productivity
4.Drive effective decision-making
8.why become a data analyst? talented gaps of skill candidates, good salaries for freshers, great future growth path
9. What recruiters look for in applicants: Problem-Solving Skills, Analytical Mind, Maths and Statistic Skills, Communication (both oral and written), Teamwork Abilities
10. Skill is required for Data analytics?
1.) Analytical Skills
2.) Numeracy Skills
3.) Technical and Computer Skills
4.) Attention to Details
5.) Business Skills
6.) Communication Skills
11. Data analytics tools
1.SAS: SAS (Statistical Analysis System) is a software suite developed by SAS Institute. sas language can be defined as a programming language in the computing field. This language is generally used for the purpose of statistical analysis. The language has the ability to read data from databases and common spreadsheets.
2. R: R is a programming language and software environment for statistical analysis, graphics representation and reporting.R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows, and Mac.
3.PYTHON: Python is a popular programming language Python is a powerful, flexible, open-sources language that is easy to use,
and has a powerful library for data manipulation and analysis.
4.TABLEAU: Tableau Software is a software company that produces interactive data visualization products focused on business intelligence.
What Is Data Science? | Introduction to Data Science | Data Science For Begin...Simplilearn
This Data Science Presentation will help you in understanding what is Data Science, why we need Data Science, prerequisites for learning Data Science, what does a Data Scientist do, Data Science lifecycle with an example and career opportunities in Data Science domain. You will also learn the differences between Data Science and Business intelligence. The role of a data scientist is one of the sexiest jobs of the century. The demand for data scientists is high, and the number of opportunities for certified data scientists is increasing. Every day, companies are looking out for more and more skilled data scientists and studies show that there is expected to be a continued shortfall in qualified candidates to fill the roles. So, let us dive deep into Data Science and understand what is Data Science all about.
This Data Science Presentation will cover the following topics:
1. Need for Data Science?
2. What is Data Science?
3. Data Science vs Business intelligence
4. Prerequisites for learning Data Science
5. What does a Data scientist do?
6. Data Science life cycle with use case
7. Demand for Data scientists
This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course.
Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
The Data Science with python is recommended for:
1. Analytics professionals who want to work with Python
2. Software professionals looking to get into the field of analytics
3. IT professionals interested in pursuing a career in analytics
4. Graduates looking to build a career in analytics and data science
5. Experienced professionals who would like to harness data science in their fields
This presentation briefly explains the following topics:
Why is Data Analytics important?
What is Data Analytics?
Top Data Analytics Tools
How to Become a Data Analyst?
What Is Data Science? | Introduction to Data Science | Data Science For Begin...Simplilearn
This Data Science Presentation will help you in understanding what is Data Science, why we need Data Science, prerequisites for learning Data Science, what does a Data Scientist do, Data Science lifecycle with an example and career opportunities in Data Science domain. You will also learn the differences between Data Science and Business intelligence. The role of a data scientist is one of the sexiest jobs of the century. The demand for data scientists is high, and the number of opportunities for certified data scientists is increasing. Every day, companies are looking out for more and more skilled data scientists and studies show that there is expected to be a continued shortfall in qualified candidates to fill the roles. So, let us dive deep into Data Science and understand what is Data Science all about.
This Data Science Presentation will cover the following topics:
1. Need for Data Science?
2. What is Data Science?
3. Data Science vs Business intelligence
4. Prerequisites for learning Data Science
5. What does a Data scientist do?
6. Data Science life cycle with use case
7. Demand for Data scientists
This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course.
Why learn Data Science?
Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
The Data Science with python is recommended for:
1. Analytics professionals who want to work with Python
2. Software professionals looking to get into the field of analytics
3. IT professionals interested in pursuing a career in analytics
4. Graduates looking to build a career in analytics and data science
5. Experienced professionals who would like to harness data science in their fields
This presentation briefly explains the following topics:
Why is Data Analytics important?
What is Data Analytics?
Top Data Analytics Tools
How to Become a Data Analyst?
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...Edureka!
Data Analytics for R Course: https://www.edureka.co/r-for-analytics
This Edureka Tutorial on Data Analytics for Beginners will help you learn the various parameters you need to consider while performing data analysis.
The following are the topics covered in this session:
Introduction To Data Analytics
Statistics
Data Cleaning and Manipulation
Data Visualization
Machine Learning
Roles, Responsibilities and Salary of Data Analyst
Need of R
Hands-On
Statistics for Data Science: https://youtu.be/oT87O0VQRi8
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It is an introduction to Data Analytics, its applications in different domains, the stages of Analytics project and the different phases of Data Analytics life cycle.
I deeply acknowledge the sources from which I could consolidate the material.
Two hour lecture I gave at the Jyväskylä Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning.
See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)
Data Analytics PowerPoint Presentation SlidesSlideTeam
This complete deck is oriented to make sure you do not lag in your presentations. Our creatively crafted slides come with apt research and planning. This exclusive deck with twenty slides is here to help you to strategize, plan, analyse, or segment the topic with clear understanding and apprehension. Utilize ready to use presentation slides on Data Analytics PowerPoint Presentation Slides with all sorts of editable templates, charts and graphs, overviews, analysis templates. It is usable for marking important decisions and covering critical issues. Display and present all possible kinds of underlying nuances, progress factors for an all inclusive presentation for the teams. This presentation deck can be used by all professionals, managers, individuals, internal external teams involved in any company organization.
Introduction to Data Science and AnalyticsSrinath Perera
This webinar serves as an introduction to WSO2 Summer School. It will discuss how to build a pipeline for your organization and for each use case, and the technology and tooling choices that need to be made for the same.
This session will explore analytics under four themes:
Hindsight (what happened)
Oversight (what is happening)
Insight (why is it happening)
Foresight (what will happen)
Recording http://t.co/WcMFEAJHok
What is Data analytics? How is data analytics a better career option?Aspire Techsoft Academy
Are you looking for the Best Data analytics Training Institute in Pune Aspire Techsoft offers you the best SAS Data Analytics Certification Training in Pune with Certified expert faculties.
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytic...Edureka!
Data Analytics for R Course: https://www.edureka.co/r-for-analytics
This Edureka Tutorial on Data Analytics for Beginners will help you learn the various parameters you need to consider while performing data analysis.
The following are the topics covered in this session:
Introduction To Data Analytics
Statistics
Data Cleaning and Manipulation
Data Visualization
Machine Learning
Roles, Responsibilities and Salary of Data Analyst
Need of R
Hands-On
Statistics for Data Science: https://youtu.be/oT87O0VQRi8
Follow us to never miss an update in the future.
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
It is an introduction to Data Analytics, its applications in different domains, the stages of Analytics project and the different phases of Data Analytics life cycle.
I deeply acknowledge the sources from which I could consolidate the material.
Two hour lecture I gave at the Jyväskylä Summer School. The purpose of the talk is to give a quick non-technical overview of concepts and methodologies in data science. Topics include a wide overview of both pattern mining and machine learning.
See also Part 2 of the lecture: Industrial Data Science. You can find it in my profile (click the face)
Data Analytics PowerPoint Presentation SlidesSlideTeam
This complete deck is oriented to make sure you do not lag in your presentations. Our creatively crafted slides come with apt research and planning. This exclusive deck with twenty slides is here to help you to strategize, plan, analyse, or segment the topic with clear understanding and apprehension. Utilize ready to use presentation slides on Data Analytics PowerPoint Presentation Slides with all sorts of editable templates, charts and graphs, overviews, analysis templates. It is usable for marking important decisions and covering critical issues. Display and present all possible kinds of underlying nuances, progress factors for an all inclusive presentation for the teams. This presentation deck can be used by all professionals, managers, individuals, internal external teams involved in any company organization.
Introduction to Data Science and AnalyticsSrinath Perera
This webinar serves as an introduction to WSO2 Summer School. It will discuss how to build a pipeline for your organization and for each use case, and the technology and tooling choices that need to be made for the same.
This session will explore analytics under four themes:
Hindsight (what happened)
Oversight (what is happening)
Insight (why is it happening)
Foresight (what will happen)
Recording http://t.co/WcMFEAJHok
What is Data analytics? How is data analytics a better career option?Aspire Techsoft Academy
Are you looking for the Best Data analytics Training Institute in Pune Aspire Techsoft offers you the best SAS Data Analytics Certification Training in Pune with Certified expert faculties.
An efficient data science team is crucial for deriving value from the humongous data a business collect. Learn how the data science team can help in this regard.
Best Data Science Hybrid Course in Pune
Data Science, in its simpler terms, is about generating critical business value from the data through various creative ways. It can also be defined as a mix of data research, algorithms, and technology to solve complex analytical issues. Data is being generated by Companies at an exponential pace. The usable Data form can be different for different sections of people working in an organization.
Data Science Classes help us to explore the data to a granular form and find the needed insights. Data Science is about being analytical or inquisitive wherein asking new questions, doing further explorations, and continuing learning is a part of the job for Data Scientists.
According to Harward Business Review, Data Scientist is the Sexiest Job of the 21st Century.
According to Forbes, IBM Predicts Demand For Data Scientists Will Soar 28% By 2020
GET FRONTLINE DATA SCIENCE TRAINING IN PUNE AT 3RI TECHNOLOGIES
Data Science is a trending niche, for it promises notable mileage for the business economy! It is rather ironic that data which was considered a burden to manage and store only about a few decades ago is now viewed as a resource; courtesy of course to data scientists. They have brought about a paradigmatic change through their skills which allow them to derive the value from raw data. It is important to mention that ‘Raw Data’ is clueless to most laymen, including the high echelons in business management; but when processed through Data Science Tools, it renders value that is precious and immense for the decision-makers and salesmen. They are all riding on the Professionalism of the Data Scientists and this generates the demand of the latter! 3RI Technologies is the leading institution offering Data Science Classes in Pune and fresh graduates as well as Working Professionals can enroll for it.
WHAT IS DATA SCIENCE?
Today, Data Science is a much-talked subject and its significance is being deliberated among the business managers who are eager to hire a brilliant professional onboard their firm. Data Science is a milieu space that is shared by the distinct yet related domains of statistics & applicative mathematics, computer programming frameworks and tools, data metrics, and analytics. Machine Learning & associated automation underpins all the above-listed fields, almost as a generic derivative; because it is through this channel that the good results are accrued in favor of the business clients. What are these good results? Let’s talk about them!
Trending smart services that are propelling businesses around the world such as SEO, SMO, SMM, SEM and CRM, all revolve around the ability to generate leads of authentic value for the commerce banners. The web developers have been doing well through their professional conduct for their clients but they in turn actively seek the ‘Meaningful Data’ about the existing and potential customers, the market trends, and the competition figures of the biz rivals. Here, Data Sc
Following the advice in this learn guide on how to become a data analyst will put you on the right path to being a professional data scientist. No matter what sector you work in, becoming a data analyst is a rewarding path to take. Explore our in-depth learn guide on "How to Become a Data Analyst" to get started with your career if you want to learn more about how to develop a successful career in this sector and discover the numerous courses available to get needed skills and expertise. Learn all the information you require to start your career, including the skills and how to acquire them.
Data Science is in high demand, the melting pot
of complex skills requires a qualified data scientist have made them the unicorns in today's data-driven landscape.
Navigating the Data Analyst Job Market in 2023- A Comprehensive GuideOptnation
In 2023, the job market for data analysts is experiencing unprecedented growth, fueled by the increasing reliance on data-driven decision-making across various industries. Data analysts play a crucial role in extracting valuable insights from vast amounts of data, aiding businesses in making informed choices. If you're considering a career as a data analyst or looking for entry-level opportunities.Visit at: https://www.optnation.com/blog/navigating-the-data-analyst-job-market-in-2023-a-comprehensive-guide/
Big data jobs are taking the highest rankings in the job market. Learn how you can excel in big data job roles as analysts, scientists, or engineers here.
What are Entry Level Data Analyst Jobs?: A Guide Skills optnation1
Paid internships and employment training programmes that are directly related to their field of study are permitted for international students holding F-1 student visas, provided that the courses fall under the category of Optional Practical Training to their major subjects of study. You can search for remote data analyst jobs and other OPT positions in the USA with similar specialisations.
Take the first step towards a rewarding career in data analytics with APTRON Solutions' Data Analytics Course in Noida. Whether you are a beginner or an experienced professional, our comprehensive training program will empower you to harness the power of data and drive business success. Enroll now and unlock a world of opportunities in the dynamic field of data analytics!
Data Analytics has become a crucial part of the IT industry, as businesses strive to extract meaningful insights from the massive amounts of data they generate. APTRON's Data Analytics Training in Gurgaon is designed to equip learners with the knowledge and skills required to become proficient in the field.
Unlocking Insights_ The Power of Data Analytics in the Modern World.pptxAPTRON Solutions Noida
In a world overflowing with data, the ability to extract meaningful information is a valuable skill. Data Analytics Training in Noida at APTRON Solutions is your gateway to a rewarding career in this ever-evolving field. Our commitment to excellence, practical approach, and industry connections make us the ideal choice for aspiring data analysts in Noida. Join us today and embark on a journey towards becoming a proficient data analyst ready to tackle the challenges of tomorrow's data-driven world. Your future in data analytics starts here at APTRON Solutions Noida!
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Difference B/w Data Analytics, Data Analysis, Data Mining, Data Science, Machine Learning, and Big Data
The most popular and rapidly evolving technologies in the world are Data Analytics, Data Analysis, Data Mining, Data Science, Machine Learning, and Big Data. All firms, large and small, are increasingly looking for IT experts who can filter through the data and help with the efficient implementation of sound business decisions. In light of the current competitive environment, Data Analytics, Data Analysis, Data Mining, Data Science, Machine Learning, and Big Data are essential technologies that drive company growth and development. In this topic, “Difference Between Data Analytics, Data Analysis, Data Mining, Data Science, Machine Learning, And Big Data,” we will examine the key definitions and skills needed to obtain them. We will also examine the main differences between Data Analytics, Data Analysis, Data Mining, Data Science, Machine Learning, and Big Data. So let’s start by briefly introducing each concept.
Data Analysis vs Data Analytics
Data Analysis is the process of analyzing, organizing, and manipulating a collection of data to extract relevant information. An “Analytics platform” is a piece of software that enables data and statistics to be generated and examined systematically, whereas a “business analyst” is a person who applies an analytical method to a collection of information for a specific goal. As this is becoming increasingly popular the corporate sector has started to broadly accept it. Data Analysis makes it easy to understand the data. It provides an important historical context for understanding what has occurred recent past. To master Power BI check out Power BI Online Course
Data Analytics includes both decision-making processes and performance enhancement through relevant forecasts. Businesses may utilize data analytics to enhance business decisions, evaluate market trends, and analyze customer satisfaction, all of which can lead to the creation of new, enhanced products and services. Using Data Analytics, it is possible to make more accurate forecasts for the future by examining previous data. To master Data Analytics Skills visit Data Analytics Course in Pune
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Data Analytics
Data Analysis
Data Analytics is analytics that is used to make conclusions based on data.
Data Analysis is a subset of data analytics that is used to analyze data and derive specific insights from it.
Using historical data and customer expectations, businesses may develop a solid business strategy.
Making the most of historical data helps organizations identify new possibilities promote business growth and make more effective decisions.
The term “data analytics” refers to the collecting and assessment of data that involves one or more users.
Data Science - Part I - Sustaining Predictive Analytics CapabilitiesDerek Kane
This is the first lecture in a series of data analytics topics and geared to individuals and business professionals who have no understand of building modern analytics approaches. This lecture provides an overview of the models and techniques we will address throughout the lecture series, we will discuss Business Intelligence topics, predictive analytics, and big data technologies. Finally, we will walk through a simple yet effective example which showcases the potential of predictive analytics in a business context.
This comprehensive program covers essential aspects of performance marketing, growth strategies, and tactics, such as search engine optimization (SEO), pay-per-click (PPC) advertising, content marketing, social media marketing, and more
The Impact of Artificial Intelligence on Modern Society.pdfssuser3e63fc
Just a game Assignment 3
1. What has made Louis Vuitton's business model successful in the Japanese luxury market?
2. What are the opportunities and challenges for Louis Vuitton in Japan?
3. What are the specifics of the Japanese fashion luxury market?
4. How did Louis Vuitton enter into the Japanese market originally? What were the other entry strategies it adopted later to strengthen its presence?
5. Will Louis Vuitton have any new challenges arise due to the global financial crisis? How does it overcome the new challenges?Assignment 3
1. What has made Louis Vuitton's business model successful in the Japanese luxury market?
2. What are the opportunities and challenges for Louis Vuitton in Japan?
3. What are the specifics of the Japanese fashion luxury market?
4. How did Louis Vuitton enter into the Japanese market originally? What were the other entry strategies it adopted later to strengthen its presence?
5. Will Louis Vuitton have any new challenges arise due to the global financial crisis? How does it overcome the new challenges?Assignment 3
1. What has made Louis Vuitton's business model successful in the Japanese luxury market?
2. What are the opportunities and challenges for Louis Vuitton in Japan?
3. What are the specifics of the Japanese fashion luxury market?
4. How did Louis Vuitton enter into the Japanese market originally? What were the other entry strategies it adopted later to strengthen its presence?
5. Will Louis Vuitton have any new challenges arise due to the global financial crisis? How does it overcome the new challenges?
Exploring Career Paths in Cybersecurity for Technical CommunicatorsBen Woelk, CISSP, CPTC
Brief overview of career options in cybersecurity for technical communicators. Includes discussion of my career path, certification options, NICE and NIST resources.
New Explore Careers and College Majors 2024.pdfDr. Mary Askew
Explore Careers and College Majors is a new online, interactive, self-guided career, major and college planning system.
The career system works on all devices!
For more Information, go to https://bit.ly/3SW5w8W
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About Hector Del Castillo
Hector is VP of Professional Development at the PMI Silver Spring Chapter, and CEO of Bold PM. He's a mid-market growth product executive and changemaker. He works with mid-market product-driven software executives to solve their biggest growth problems. He scales product growth, optimizes ops and builds loyal customers. He has reduced customer churn 33%, and boosted sales 47% for clients. He makes a significant impact by building and launching world-changing AI-powered products. If you're looking for an engaging and inspiring speaker to spark creativity and innovation within your organization, set up an appointment to discuss your specific needs and identify a suitable topic to inspire your audience at your next corporate conference, symposium, executive summit, or planning retreat.
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3. DATA?
In computing, data is information that has been translated
into a form that is efficient for movement or processing.Data
can exist in a variety of forms as numbers or text on pieces of
paper, as bits and bytes stored in electronic memory, or as
facts stored in a person's mind.
4. ANALYTICS?
Analytics is the discovery, interpretation, and communication
of meaningful patterns in data and applying those patterns
towards effective decision making .Analytics is an
encompassing and multidimensional field that uses
mathematics, statistics, predictive modeling and machine
learning techniques to find meaningful patterns and
knowledge in recorded data.
5. Types of Analytics
1
2 3
Analytics
Prescriptive Analytics
Enabling smart decisions based on data
What should we do
Descriptive Analytics
Mining data to provide business
insights?
What has happened?
Predictive Analytics
predicting the future
based on historical
patterns
What could happen?
7. What is DATA analytics?
Data analysis is a process of inspecting,
cleansing, transforming, and modeling data.
Data analytics refers to qualitative and
quantitative techniques and processes used
to enhance productivity and business gain
8. Why Data Analytics
Data Analytics is needed in Business to Consumer
applications (B2C). Organisations collect data that they have
gathered from customers, businesses, economy and practical
experience. Data is then processed after gathering and is
categorised as per the requirement and analysis is done to
study purchase patterns and etc.
9.
10. The process of Data Analysis
Analysis refers to breaking a whole into its separate
components for individual examination. Data analysis is a
process for obtaining raw data and converting it into
information useful for decision-making by users. There are
several phases that can be distinguished :Data requirements,
Data collection ,Data processing ,Data cleaning, Exploratory
data analysis,
Modeling and algorithms , Data product ,Communication
11. Scope of Data Analytics
Bright future of data analytics, many professionals and students are interested in a
career in data analytics. Any person who likes to work on numbers, has a logical
thinking, can understand figures and can turn them into actionable insights, has a
good future in this field. A proper training of the tools of data analytics would be
required to begin with. Since it is a course that requires effort to learn and get
certified, there is always dearth of qualified professionals. Being a relatively new
field also, the demand for such professionals is more than the current supply.
Higher demand also means higher salaries.
12. Importance Data Analytics
● Predict customer trends and behaviours
● Analyse, interpret and deliver data in meaningful ways
● Increase business productivity
● Drive effective decision-making
20. Demand of Data Analysis Jobs
Data analysis jobs are everywhere and they are bound to
increase! Here are some facts and figures to highlight this:
“2.5 billion gigabytes (GB) of data was generated
every day in 2012. (IBM) International Business Machines”
21. Going by the statistics, by 2020, about 1.7 megabytes of new information will be
created every second for every human! Well, that’s huge. Very huge. Companies
will need more and more data specialists to analysis and manage the data
generated.
22. Basic Skills required to start your career in data analytics
● How to set up data structure?
● How to create data visualizations
● Knowledge with database languages like SQL,
MySQL
● knowledge of big data tools like Hive or Pig
● Know statistical programming languages like R or
Python
● Understanding of machine learning tools &
techniques
23. What recruiters look for in applicants
Problem Solving Skills: When working with complex sets of data, companies rely on
analysts to interpret the numbers and figures to find solutions to their problems. Your
primary job is to read between the numbers and datasets to find the answers that
inexperienced analysts can't see. You are who they turn to when they need a
complex problem solved with data, and you could potentially shape the future of the
company.
Analytical Mind: This goes hand-in-hand with the problem-solving skills needed. An
optimal candidate for any analytics position must have a mind that naturally looks for
answers and connections between data sets. This is incredibly useful, especially
when handling large sets of data. You must be able to decipher and make
connections that nobody else can.
24. Maths and Statistic Skills:It goes without saying that if you want to be an
effective data analyst or scientist, you must be able to do the math to analyze
and interpret the data. Although a majority of calculations are completed with
computer programs, a solid foundation and understanding of mathematics or
statistics will take you far in this field.
Communication (both oral and written): Once you find solutions and make
connections using the data you won't be keeping it to yourself. You must be
able to succinctly and accurately explain sophisticated mathematical and
statistical principles that other departments can understand.Communication
skills go a long way in any career and data analysis is no exception.
Teamwork Abilities: More times than not, you never work alone. You will be
a part of a team of data specialists, and it is vital to the success of the team
and organization that you can all work together to solve complex problems.
25. Skill is required for Data analytics ?
1.) Analytical Skills
2.) Numeracy Skills
3.) Technical and Computer Skills
4.) Attention to Details
5.) Business Skills
6.) Communication Skills
26. CAREER
Data analysis is a rapidly growing field and highly skilled
analysts in increased demand across all sectors. This is
evident from the average salary of a data analyst in India.
This implies that you would find many opportunities but you
will still have to be outstanding and exhibit excellent data
analytics skills to be successful as a data analyst.
29. A data scientist is a person who utilises the data in possession of the organisation
to design business-oriented learning models and types of machinery.
30. Data analytics role expects you to prepare insights from the available data which
directly impacts decisions in businesses. There is direct involvement of data analysts
in everyday business activities.
31. The Truth About Data Analytics:
Data analytics for businesses that want to make good use of the data that they are
taking in. Businesses that can use data analytics properly are more likely than others to
succeed and thrive. But with all of the advantages of data analytics, the key benefits can
be described in this way:
● Data analytics reduces the costs associated with running a business.
● It cuts down on the time needed to come to strategy-defining decisions.
● Data analytics help to more-accurately define customer trends. Determining
the Effectiveness of Your Analytics Program
Given the growing familiarity and popularity of data analytics, there are a number of
advanced analytics programs available on the market. As such, there are certain traits
to look for in any analytics solution that will help you gage just how effective it will be
in improving your business.
36. SAS (Statistical Analysis System) is a software suite developed by
SAS institute. SAS language can be defined as a programming language in the
computing field. This language is generally used for the purpose of statistical
analysis.The language has an ability to read the data from databases and common
spreadsheets.
The output of the statistical analysis performed is represented in the form of graphs.
The data is given in the form of RTF, PDF, and HTML files. The compilers, under
which the SAS programming language runs, can be used on a wide variety of
platforms, including Linux, mainframe computers, Microsoft Windows, and a number
of other UNIX.
37.
38. R is a programming language and software environment for statistical analysis, graphics
representation and reporting.R is freely available under the GNU General Public License,
and pre-compiled binary versions are provided for various operating systems like Linux,
Windows and Mac.
Features of R
The following are the important features of R −
● R is a well-developed, simple and effective programming language which includes
conditionals, loops, user defined recursive functions and input and output facilities.
● R has an effective data handling and storage facility,
● R provides a suite of operators for calculations on arrays, lists, vectors and matrices.
● R provides a large, coherent and integrated collection of tools for data analysis.
● R provides graphical facilities for data analysis and display either directly at the computer or
39.
40.
41.
42.
43.
44. Python is a popular programming language python is a
powerful,flexible,open-sources language that is easy to use,
and has a powerful libraries for data manipulation and analysis.
45. Tableau Software is a software company that produces
interactive data visualization products focused on business
intelligence.