This document provides an introduction to business analytics, including the types (descriptive, predictive, and prescriptive), tools (data visualization, business intelligence reporting software, self-service analytics platforms, statistical analysis, and big data platforms), roles (business user, project sponsor, project manager, business intelligence analyst, database administrator, data engineer, and data scientist), and lifecycle (problem definition, research, resource assessment, data acquisition, data storage, exploratory analysis, modeling, implementation, and developing deliverables).
The presentation is about the career path in the field of Data Science. Data Science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
FUTURE OF DATA SCIENCE IN INDIA
DATA SCIENCE
It is a tool that uses all kinds of data, algorithms and scientific methods. It is a very important tool as it combines two of the most important things in technology and modern science that is mathematics and computer science together. Organizing, data delivery and packaging are the three most important components involved in data science. Data Science handles data works on them and makes conclusion based on the data.
Big data is a huge volume of heterogenous data often generated at high speed.Big data cannot be handles with traditional data analytic tools. Hadoop is one of the mostly used big data analytic tool.Map Reduce, hive, hbase are also the tools for analysis in big data.
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?
Leveraging Data Science in the Automotive IndustryDomino Data Lab
Cars.com Inc. is a decision engine for car buyers and a growth engine for our partners. Data Science is the bread and butter of any decision engine and Cars is no different. In this talk, I will discuss how we quantify various parameters of a car and plan to make use of all the data in hand to put predictive models at various stages of a users’ automobile lifecycle. This talk will also cater to students looking to gain knowledge on how data science is utilized at scale while still following certain processes and leading the way for business and product partners.
The presentation is about the career path in the field of Data Science. Data Science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
FUTURE OF DATA SCIENCE IN INDIA
DATA SCIENCE
It is a tool that uses all kinds of data, algorithms and scientific methods. It is a very important tool as it combines two of the most important things in technology and modern science that is mathematics and computer science together. Organizing, data delivery and packaging are the three most important components involved in data science. Data Science handles data works on them and makes conclusion based on the data.
Big data is a huge volume of heterogenous data often generated at high speed.Big data cannot be handles with traditional data analytic tools. Hadoop is one of the mostly used big data analytic tool.Map Reduce, hive, hbase are also the tools for analysis in big data.
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?
Leveraging Data Science in the Automotive IndustryDomino Data Lab
Cars.com Inc. is a decision engine for car buyers and a growth engine for our partners. Data Science is the bread and butter of any decision engine and Cars is no different. In this talk, I will discuss how we quantify various parameters of a car and plan to make use of all the data in hand to put predictive models at various stages of a users’ automobile lifecycle. This talk will also cater to students looking to gain knowledge on how data science is utilized at scale while still following certain processes and leading the way for business and product partners.
Effectiveness of Data Analytics and Big Data in United States Presidential Elections, Polls, Voting and Campaigns. U.S. presidential elections are the most talked about topic now a days. Who will win race? Donald Trump or Hillary Clinton ? This presentation gives an insight on how people can utilize the data analytics approaches to achieve specific goals and get insight to the target users.
This presentation is an Introduction to the importance of Data Analytics in Product Management. During this talk Etugo Nwokah, former Chief Product Officer for WellMatch, covered how to define Data Analytics why it should be a first class citizen in any software organization
every business needs a data analytics to get a detailed value of cost and profits. we will study the importance in detail in this particular presentation.
Graph technology has truly burst onto the scene with diverse new products and services, proving that graph is relevant and that not all graph use cases are equal. Previously relegated to niche implementations and science projects, graph now finds itself deployed as the foundational technology for enterprise analytics solutions and enterprise Data Fabric strategies. It is no surprise that many are calling 2018 “The Year of the Graph”.
In this presentation, I have talked about Big Data and its importance in brief. I have included the very basics of Data Science and its importance in the present day, through a case study. You can also get an idea about who a data scientist is and what all tasks he performs. A few applications of data science have been illustrated in the end.
Introduction to Data Science (Data Summit, 2017)Caserta
At DBTA's 2017 Data Summit in New York, NY, Caserta Founder & President, Joe Caserta, and Senior Architect, Bill Walrond, gave a pre-conference workshop presenting the ins and outs of data science. Data scientist has been dubbed the "sexiest" job of the 21st century, but it requires an understanding of many different elements of data analysis. This presentation dives into the fundamentals of data exploration, mining, and preparation, applying the principles of statistical modeling and data visualization in real-world applications.
Accelerating Insight - Smart Data Lake Customer Success StoriesCambridge Semantics
At Gartner Data & Analytics Summit 2017 Alok Prasad, President, was joined by Peter Horowitz of PricewaterhouseCoopers in presenting a session on how Cambridge Semantics' in-memory, massively parallel, semantic graph-based platform delivers an accelerating edge to data-driven organizations, while maintaining trust with security and governance.
Introduction to Analytic fields. Data Analytics. What is Analytics. What it takes to be a Analyst, Different Profiles in Analytics fileds, Data science, data analytics, big data profiles, etc
This Presentation gives an insight into what is big data, data analytics, difference between big data and data science.And also salary trends in big data analytics.
Be Digital or Die - Predictive Analytics for Digital TransformationFintricity
A look at leveraging big data and predictive analytics for digital transformation. This deck was presented at the Predictive Analytics & Innovation Summit in London. 10th May 2016, by Alpesh Doshi, Founder of Fintricity.
HR / Talent Analytics orientation given as a guest lecture at Management Institute for Leadership and Excellence (MILE), Pune. This presentation covers aspects like:
1. Core concepts, terminologies & buzzwords
- Business Intelligence, Analytics
- Big Data, Cloud, SaaS
2. Analytics
- Types, Domains, Tools…
3. HR Analytics
- Why? What is measured?
- How? Predictive possibilities…
4. Case studies
5. HR Analytics org structure & delivery model
Effectiveness of Data Analytics and Big Data in United States Presidential Elections, Polls, Voting and Campaigns. U.S. presidential elections are the most talked about topic now a days. Who will win race? Donald Trump or Hillary Clinton ? This presentation gives an insight on how people can utilize the data analytics approaches to achieve specific goals and get insight to the target users.
This presentation is an Introduction to the importance of Data Analytics in Product Management. During this talk Etugo Nwokah, former Chief Product Officer for WellMatch, covered how to define Data Analytics why it should be a first class citizen in any software organization
every business needs a data analytics to get a detailed value of cost and profits. we will study the importance in detail in this particular presentation.
Graph technology has truly burst onto the scene with diverse new products and services, proving that graph is relevant and that not all graph use cases are equal. Previously relegated to niche implementations and science projects, graph now finds itself deployed as the foundational technology for enterprise analytics solutions and enterprise Data Fabric strategies. It is no surprise that many are calling 2018 “The Year of the Graph”.
In this presentation, I have talked about Big Data and its importance in brief. I have included the very basics of Data Science and its importance in the present day, through a case study. You can also get an idea about who a data scientist is and what all tasks he performs. A few applications of data science have been illustrated in the end.
Introduction to Data Science (Data Summit, 2017)Caserta
At DBTA's 2017 Data Summit in New York, NY, Caserta Founder & President, Joe Caserta, and Senior Architect, Bill Walrond, gave a pre-conference workshop presenting the ins and outs of data science. Data scientist has been dubbed the "sexiest" job of the 21st century, but it requires an understanding of many different elements of data analysis. This presentation dives into the fundamentals of data exploration, mining, and preparation, applying the principles of statistical modeling and data visualization in real-world applications.
Accelerating Insight - Smart Data Lake Customer Success StoriesCambridge Semantics
At Gartner Data & Analytics Summit 2017 Alok Prasad, President, was joined by Peter Horowitz of PricewaterhouseCoopers in presenting a session on how Cambridge Semantics' in-memory, massively parallel, semantic graph-based platform delivers an accelerating edge to data-driven organizations, while maintaining trust with security and governance.
Introduction to Analytic fields. Data Analytics. What is Analytics. What it takes to be a Analyst, Different Profiles in Analytics fileds, Data science, data analytics, big data profiles, etc
This Presentation gives an insight into what is big data, data analytics, difference between big data and data science.And also salary trends in big data analytics.
Be Digital or Die - Predictive Analytics for Digital TransformationFintricity
A look at leveraging big data and predictive analytics for digital transformation. This deck was presented at the Predictive Analytics & Innovation Summit in London. 10th May 2016, by Alpesh Doshi, Founder of Fintricity.
HR / Talent Analytics orientation given as a guest lecture at Management Institute for Leadership and Excellence (MILE), Pune. This presentation covers aspects like:
1. Core concepts, terminologies & buzzwords
- Business Intelligence, Analytics
- Big Data, Cloud, SaaS
2. Analytics
- Types, Domains, Tools…
3. HR Analytics
- Why? What is measured?
- How? Predictive possibilities…
4. Case studies
5. HR Analytics org structure & delivery model
What is "Next Generation" Analytics? How does it fit with my Business Vision?Sparkhound Inc.
At a recent Arkansas Lunch & Learn, Sparky Business Analyst Rusty Frioux discusses Sparkhound's end-to-end Business Intelligence & Analytics approach that drives business impact through technologies like SharePoint and Power BI. Learn what Business Intelligence & Analytics is and how to build the right strategy and tools for your business.
Inspirational approaches to HR data to drive better management and decision-making. On Friday 23 September 2016 we hosted a morning seminar for senior HR managers and executives on how to create business impact through HR & People analytics.
Webinar: Business Intelligence From The Inside OutCorSourceTechPDX
There are a lot of terms thrown around in the world of business intelligence and analytics. Presented as a webinar, this deck is an introduction to the terminology and power of business intelligence to transform companies.
Looking at what is driving Big Data. Market projections to 2017 plus what is are customer and infrastructure priorities. What drove BD in 2013 and what were barriers. Introduction to Business Analytics, Types, Building Analytics approach and ten steps to build your analytics platform within your company plus key takeaways.
Basic Concepts of Business Data Analytics, Evolution of Business Analytics, Data Analytics, Business Data Analytics Applications, Scope of Business Analytics.
The majority of organizations (54%) use people analytics to improve HR effectiveness today. Organizations more frequently rely on people analytics to improve business outcomes, organizational performance and achieve labor cost savings.
People Analytics allows HR to gain a more strategic role in the organization and clearly show its impact.
Advanced organizations use data to analyze the workforce proactively, make predictions, and create and monitor comprehensive workforce plans to achieve financial success.
HR data has become an strategic priority, but it takes efforts in order to enable the usage of it.
A wireless body area network (WBAN) is a special purpose sensor network designed to operate autonomously to connect various medical sensors and appliances , located inside and outside the body.
What is big data ? | Big Data ApplicationsShilpaKrishna6
Big data is similar to ‘small data’ but bigger in size. It is a term that describes the large volume of data both structured and unstructured. Big data generates value from the storage and processing of very large quantities of digital information that cannot be analyzed with traditional computing techniques
This video will give you an idea about Data science for beginners.
Also explain Data Science Process , Data Science Job Roles , Stages in Data Science Project
MapReduce is one of the most important and major component in Hadoop Ecosystem. Whenever we are having a large set of data then in the case of the huge data set will be divided into smaller pieces and processing will be done on them in parallel in MapReduce.
NoSQL is known as Not only SQL database, provides a mechanism for storage and retrieval of data.
In this section is discussing about two data models.
Aggregate Data Models
Distribution Data Models
Key-Value data model, Document data model, Column-family stores and Graph database are come under Aggregate data Models
Distribution data Models are Sharding, Master-slave replication and Peer-peer replication
Internet of Things(IoT) Applications
IoT has many applications. This video is talking about some of the iot applications,namely
Smart Home
Smart Wearables
Smart City
Smart Grid
Connected Cars
Connected Health
Smart Retail
Smart Farming
4 pillers of iot
1. M2M
(machine to machine)
2. WSN
(wireless sensor network)
3. RFID
(radio frequency identification device)
4. SCADA
(supervisory control and data acquisition)
Different number system used in computers to represent data.
Number system are of 4 types-Decimal,Binary,Octal&Hexadecimal
visit my channel for detailed explaination of conversions of number systems
https://youtu.be/elFs55aledc
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
3. TYPES OF BUSINESS ANALYTICS
DESCRIPTIVE ANALYTICS What happened ?
PREDICTIVE ANALYTICS What might happen ?
PRESCRIPTIVE ANALYTICS What should we do ?
4. BUSINESS ANALYTICS TOOLS
DATA VISUALIZATION TOOLS
BUSINESS INTELLIGENCE REPORTING SOFTWARE
SELF-SERVICE ANALYTICS PLATFORMS
STATISTICAL ANALYSIS TOOLS
BIG DATA PLATFORMS
5. KEY ROLES FOR SUCCESSFUL
ANALYTIC PROJECT
BUSINESS USER
PROJECT SPONSER
PROJECT MANAGER
BUSINESS
INTELLIGENCE
ANALYST
DATABASE
ADMINISTRATOR(DBA)
DATA ENGINEER
DATA SCIENTIST
6. MAIN PHASES OF LIFE CYCLE
BUSINESS PROBLEM DEFINITION
RESEARCH
HUMAN RESOURCE ASSESSMENT
DATA ACQUISITION
DATA MUNGING
DATA STORAGE
EXPLORATORY DATA ANALYSIS
DATA PREPARATION FOR MODELING AND ASSESSMENT
MODELLING
IMPLEMENTATION
