The document discusses several data-related careers including Chief Data Officer, Data Analyst, Data Scientist, Data Engineer, Data Modeler, Data Architect, and Data Entry Specialist. For each role, it provides a brief description of typical tasks and the average salary. It also notes common skills and experience levels associated with higher pay for some of the roles. The document serves as an overview of the various types of data-focused jobs that have emerged with the growth of data and its importance in business.
Data analytics presentation- Management career institute PoojaPatidar11
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.
BA Case Studies Show EA-IT Value Forrester ITF09Gene Leganza
Most enterprise architecture EA literature roots EA in business goals and strategies, and the rise of business architecture initiatives promises to finally close the gap in strategic business input for architecture planning. But the increasing focus on business architecture does not mean that EA is becoming more of a business function than an IT function. Rather, business architecture initiatives will enable enterprise architects to make EA a critical IT function that positions the CIO to become an important business partner to business executives. This session discusses how business architecture can improve IT’s value at any level of IT maturity and explores several case studies to show how business architecture helps to elevate EA to the most effective tool in the CIO’s toolbox.
The one question you must never ask!" (Information Requirements Gathering for...Alan D. Duncan
Presentation from 2014 International Data Quality Summit (www.idqsummit.org, Twitter hashtag #IDQS14). Techniques for business analysts and data scientists to facilitate better requirements gathering in data and analytic projects.
Data analytics presentation- Management career institute PoojaPatidar11
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.
BA Case Studies Show EA-IT Value Forrester ITF09Gene Leganza
Most enterprise architecture EA literature roots EA in business goals and strategies, and the rise of business architecture initiatives promises to finally close the gap in strategic business input for architecture planning. But the increasing focus on business architecture does not mean that EA is becoming more of a business function than an IT function. Rather, business architecture initiatives will enable enterprise architects to make EA a critical IT function that positions the CIO to become an important business partner to business executives. This session discusses how business architecture can improve IT’s value at any level of IT maturity and explores several case studies to show how business architecture helps to elevate EA to the most effective tool in the CIO’s toolbox.
The one question you must never ask!" (Information Requirements Gathering for...Alan D. Duncan
Presentation from 2014 International Data Quality Summit (www.idqsummit.org, Twitter hashtag #IDQS14). Techniques for business analysts and data scientists to facilitate better requirements gathering in data and analytic projects.
Semantic 'Radar' Steers Users to Insights in the Data LakeCognizant
By infusing information with intelligence, users can discover meaning in the digital data that envelops people, organizations, processes, products and things.
A presentation on Talent Analytics or HR Analytics. This presentation gives various tools and parameters involved in HR Analytics and their Application.
The Definitive Guide to Data Modeling for Business IntelligenceEran Levy
Data modelling is one of the most important steps in preparing data for BI analysis. Anyone working with data - either as an analyst or as a passive 'consumer' - should take a few moments to check out this slideshow and learn the bare basics of data modelling for business intelligence.
To learn more about data modeling, watch our free webinar at http://bit.ly/1N095Sn
Do you want to understand the emerging new data-driven jobs? This presentation discusses the emerging roles of Data Science and Data Engineering, and how they are related to Business Intelligence and Big Data. We will talk about skills and background needed for the jobs, and what education and certification is important.
Small and medium enterprise business solutions using data visualizationjournalBEEI
The small and medium enterprise (SME) companies optimize performance using different automated systems to highlight the operations concerns. However, lack of efficient visualization in reporting results in slow feedbacks, difficulties in extracting root cause, and minimal corrective actions. To complicate matters, the data heterogeneity has intensely increased, and it is produced in a fast manner making it unmanageable if the traditional methods of analytics are applied. Hence, we propose the use of a dashboard that can summarize the operational events using real-time data based on the data visualization approach. This proposed solution summarizes the raw data, which allows the user to make informed decisions that can give a positive impact on business performance. An interactive intelligent dashboard for SME (iid-SME) is developed to tackle issues such as measurement of cases completed, the duration of time needed to solve a case, the individual performance of handling cases and other tasks as a proof of concept. From the result, the implementation of the iid-SME approach simplifies the conveyance of the message and helps the SME personnel to make decisions. With the positive feedback obtained, it is envisaged that such a solution can be further employed for SME improvement for better profit and decision making.
ADV Slides: What the Aspiring or New Data Scientist Needs to Know About the E...DATAVERSITY
Many data scientists are well grounded in creating accomplishment in the enterprise, but many come from outside – from academia, from PhD programs and research. They have the necessary technical skills, but it doesn’t count until their product gets to production and in use. The speaker recently helped a struggling data scientist understand his organization and how to create success in it. That turned into this presentation, because many new data scientists struggle with the complexities of an enterprise.
Incorporating SAP Metadata within your Information ArchitectureChristopher Bradley
Incorporating SAP Metadata into your overall Information Management architecture. Case study from BP and IPL presented at Enterprise Data World, Tampa, FL April 2009
Data modelling has been around since the mid 1970's but in many organisations there is considerable scepticism and downright distrust regarding the place dta modelling should occupy. So why does data modelling still have to be "sold" in many companies, and in others people simply don't believe it's necessary " the software package has all I need"! This paper looks at the failure of organisations to capitalise on the benefits data modelling can yield and examines where in the changing information systems landscape modelling is relevant.
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.
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.
A data analyst collects, cleans, and interprets data sets to provide an answer or solve an issue. They work in a variety of industries, including business, banking, criminal justice, science, medical, and government. Data analyst jobs in US can take various shapes depending on the question you're attempting to answer. Being a data analyst might also lead to other employment opportunities. Many data analysts eventually become data scientists.
Semantic 'Radar' Steers Users to Insights in the Data LakeCognizant
By infusing information with intelligence, users can discover meaning in the digital data that envelops people, organizations, processes, products and things.
A presentation on Talent Analytics or HR Analytics. This presentation gives various tools and parameters involved in HR Analytics and their Application.
The Definitive Guide to Data Modeling for Business IntelligenceEran Levy
Data modelling is one of the most important steps in preparing data for BI analysis. Anyone working with data - either as an analyst or as a passive 'consumer' - should take a few moments to check out this slideshow and learn the bare basics of data modelling for business intelligence.
To learn more about data modeling, watch our free webinar at http://bit.ly/1N095Sn
Do you want to understand the emerging new data-driven jobs? This presentation discusses the emerging roles of Data Science and Data Engineering, and how they are related to Business Intelligence and Big Data. We will talk about skills and background needed for the jobs, and what education and certification is important.
Small and medium enterprise business solutions using data visualizationjournalBEEI
The small and medium enterprise (SME) companies optimize performance using different automated systems to highlight the operations concerns. However, lack of efficient visualization in reporting results in slow feedbacks, difficulties in extracting root cause, and minimal corrective actions. To complicate matters, the data heterogeneity has intensely increased, and it is produced in a fast manner making it unmanageable if the traditional methods of analytics are applied. Hence, we propose the use of a dashboard that can summarize the operational events using real-time data based on the data visualization approach. This proposed solution summarizes the raw data, which allows the user to make informed decisions that can give a positive impact on business performance. An interactive intelligent dashboard for SME (iid-SME) is developed to tackle issues such as measurement of cases completed, the duration of time needed to solve a case, the individual performance of handling cases and other tasks as a proof of concept. From the result, the implementation of the iid-SME approach simplifies the conveyance of the message and helps the SME personnel to make decisions. With the positive feedback obtained, it is envisaged that such a solution can be further employed for SME improvement for better profit and decision making.
ADV Slides: What the Aspiring or New Data Scientist Needs to Know About the E...DATAVERSITY
Many data scientists are well grounded in creating accomplishment in the enterprise, but many come from outside – from academia, from PhD programs and research. They have the necessary technical skills, but it doesn’t count until their product gets to production and in use. The speaker recently helped a struggling data scientist understand his organization and how to create success in it. That turned into this presentation, because many new data scientists struggle with the complexities of an enterprise.
Incorporating SAP Metadata within your Information ArchitectureChristopher Bradley
Incorporating SAP Metadata into your overall Information Management architecture. Case study from BP and IPL presented at Enterprise Data World, Tampa, FL April 2009
Data modelling has been around since the mid 1970's but in many organisations there is considerable scepticism and downright distrust regarding the place dta modelling should occupy. So why does data modelling still have to be "sold" in many companies, and in others people simply don't believe it's necessary " the software package has all I need"! This paper looks at the failure of organisations to capitalise on the benefits data modelling can yield and examines where in the changing information systems landscape modelling is relevant.
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.
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.
A data analyst collects, cleans, and interprets data sets to provide an answer or solve an issue. They work in a variety of industries, including business, banking, criminal justice, science, medical, and government. Data analyst jobs in US can take various shapes depending on the question you're attempting to answer. Being a data analyst might also lead to other employment opportunities. Many data analysts eventually become data scientists.
Learn All about Data Science from the Best Private University in KarnatakaREVA University
Completing Masters in Data Science degree can reshape your career path, though it demands dedication and time to gain the necessary skills and land the right job. To assist you, we've crafted a detailed plan for building a career in Data Science.
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
Emerging opportunities in the age of dataEjaz Siddiqui
We live in a data-driven world. There are more than 4 billion people around the world using the internet.
This show an unprecedented spread and growth of digital devices. These digital devices (Mobiles, Computers, Watches, IoT etc) are the factories for creating data. It means we live in the Age of Data, and it’s expanding at astonishing rates. We may need to unplug and take a break from time to time, but data never sleeps.
This generation of huge data presents many new challenges as well as opportunities. There would be huge opportunity for the people who could collect, process, manage, drive insights and make useful decisions from this data. Certain fields are becoming very important and necessary to manage and process this data.
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.
Challenges Of A Junior Data Scientist_ Best Tips To Help You Along The Way.pdfvenkatakeerthi3
One of the most fascinating fields today that is enabling businesses to improve their operations is data science.
Databases, network servers and official social media pages.
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.
Advanced Business Analytics for Actuaries - Canadian Institute of Actuaries J...Kevin Pledge
Presentation given at the Canadian Institute of Actuaries Annual Meeting in June 2013. Covers the direction business intelligence is moving in for insurance.
Computer software engineers apply engineering principles and systematic methods to develop programs and operating data for computers. If you have ever asked yourself, “What does a software engineer do?” note that daily tasks vary widely. Professionals confer with system programmers, analysts, and other engineers to extract pertinent information for designing systems, projecting capabilities, and determining performance interfaces. Computer software engineers also analyze user needs, provide consultation services to discuss design elements, and coordinate software installation. info@globalb2bcontacts.com
http://www.globalb2bcontacts.com
https://globalb2bcontacts.com/Technology-email-lists.html
https://globalb2bcontacts.com/sub-industry-email-database.html
https://globalb2bcontacts.com/email-database.html
https://globalb2bcontacts.com/Healthcare-email-list.html
Computer software engineers apply engineering principles and systematic methods to develop programs and operating data for computers. Computer software engineers also analyze user needs, provide consultation services to discuss design elements, and coordinate software installation. Designing software systems requires professionals to consider mathematical models and scientific analysis to project outcomes.
info@globalb2bcontacts.com
http://www.globalb2bcontacts.com
https://globalb2bcontacts.com/Technology-email-lists.html
https://globalb2bcontacts.com/sub-industry-email-database.html
https://globalb2bcontacts.com/email-database.html
https://globalb2bcontacts.com/Healthcare-email-list.html
Looking forward, the U.S. Computer software engineers apply engineering principles and systematic methods to develop programs and operating data for computers. If you have ever asked yourself, “What does a software engineer do?” note that daily tasks vary widely. Professionals confer with system programmers, analysts, and other engineers to extract pertinent information for designing systems, projecting capabilities, and determining performance interfaces. Computer software engineers also analyze user needs, provide consultation services to discuss design elements, and coordinate software installation.
info@globalb2bcontacts.com
http://www.globalb2bcontacts.com
https://globalb2bcontacts.com/Technology-email-lists.html
https://globalb2bcontacts.com/sub-industry-email-database.html
https://globalb2bcontacts.com/email-database.html
https://globalb2bcontacts.com/Healthcare-email-list.html
Computer software engineers apply engineering principles and systematic methods to develop programs and operating data for computers. Computer software engineers also analyze user needs, provide consultation services to discuss design elements, and coordinate software installation. Designing software systems requires professionals to consider mathematical models and scientific analysis to project outcomes.
info@globalb2bcontacts.com
http://www.globalb2bcontacts.com
https://globalb2bcontacts.com/Technology-email-lists.html
https://globalb2bcontacts.com/sub-industry-email-database.html
https://globalb2bcontacts.com/email-database.html
https://globalb2bcontacts.com/Healthcare-email-list.html
The rest of this post discusses 11 different roles that make up a fully functional social media team. But that doesn’t mean that you’ll necessarily need to hire 11 different people to achieve the outcomes you are looking for. If you’re a small business (on a budget), less persons may cover multiple roles to flesh out your strategy on a smaller scale.
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
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
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
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!
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
2. WWW.ADJIGOL.COM
Adjigol@Hotmail.com
Chief Data Officer (CDO
Data Analyt
Data Scientist
Data Engineer
Data Modeler
Data Architect
Data Entry Specialist
Data Visualization Specialist
Database Adminstrator
Database Developer
Data Warehouse Manager
Data Warehouse Developer
ETL Developer
Business Intelligence (BI) Specialist
3. WWW.ADJIGOL.COM
Adjigol@Hotmail.com
Data Careers
Every time you send a text message, type a tweet, post a Facebook photo, click a link,
or buy something online, you’re generating data. And considering there are more
than 3 billion Internet users in the world (a quantity that’s tripled in the last 12 years)
and 4.3 billion cell phone users, that’s a heck of a lot of data.
Fortunately, as data has multiplied, so has the ability to collect, organize, and analyze
it. Data storage is cheaper than ever, processing power is more massive than ever,
and tools are more accessible than ever to mine the zettabytes of available data for
business intelligence. In recent years, data analysis has done everything from predict
stock prices to prevent house fires.
The McKinsey Global Institute predicted that by 2018 the U.S. could face a shortage
of 1.5 million people who know how to leverage data analysis to make effective
decisions.
4. WWW.ADJIGOL.COM
Adjigol@Hotmail.com
Chief Data Officer
a. Work with executives, data owners, and data stewards
to achieve data accuracy and process requirement goals
for all internal and external customers and create data
management strategies.
b. Spearhead the data management activities performed by the EIM program, the
business data stewards, and data service providers.
c. Establish data policies, standards, organization, and enforcement of EIM concepts as
established by the organization.
d. Oversee the monitoring of data quality efforts within the organization and provides a
central authority for the resolution on data management issues that cannot be resolved
by the data governance council.
e. Establish data vendor management strategy and provide oversight to support
implementation by the EIM program and coordinates with the IT organization through
the CIO/CTO.
f. Lead the creation of program business definitions and data management goals and
principles for execution by the EIM program.
g. Responsible for enterprise information/data management budget and data-related
systems initiatives.
Job Description for Chief Data Officer
Develop, recommend, and implement strategic planning for short and long-term
operational and financial practice management.
Evaluate company's operational and financial performance.
Oversee support staff and develop training and performance improvement
programs.
Monitor competitive market and prepare reports analyzing the financial drivers of
business.
A Chief Data Officer earns an average salary of $179,039 per year. Most people in this
job have more than five years' experience in related jobs.
6. WWW.ADJIGOL.COM
Adjigol@Hotmail.com
Data Analyst
A data analyst uses data to acquire information about
specific topics. This usually starts with the survey
process, in which data analysts find survey
participants and gather the needed information. The
data is then interpreted and presented in forms such as charts or reports. Data analysts
may also put their survey data in online databases.
Individuals looking for data analyst jobs must be knowledgeable in computer programs
such as Microsoft Excel, Microsoft Access, SharePoint, and SQL databases. Data
analysts also must have good communication skills, as they must have an open line of
communication with the companies with which they work. Data analysts should be able
to work indoors with clients, supervisors, and managers to meet goals set by all parties.
A data analyst should be willing to work hard for the betterment of their company.
Data Analyst Tasks
Collect, analyze, and report data to meet customer needs.
Identify new sources of data and methods to improve data collection, analysis,
and reporting.
Collect customer requirements, determine technical issues, and design reports to
meet data analysis needs.
The average salary for a Data Analyst is C$53,483 per year. Skills that are associated
with high pay for this job are Data Modeling and SAS. Most people move on to other
jobs if they have more than 10 years' experience in this field.
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Data Scientist
Some companies treat the titles of “data scientist”
and “data analyst” as synonymous. But there’s
really a distinction between the two in terms of skill
set and experience.
IT data scientists are responsible for mining complex
data and providing systems-related advice for their organization. They design new ways
to incorporate vast information with a focus on information technology topics. They work
with teams of other IT professionals to manage statistical data and create different
models based on the needs of their company. They possess advanced analytical skills,
in addition to their exceptional oral and written communication abilities. They process
research information for easier consumption and transform it into actionable plans. They
also provide value to their businesses through their findings and thoughtful insights.
Data Scientist, IT Tasks
Design and build new data set processes for modeling, data mining, and
production purposes.
Determine new ways to improve data and search quality, and predictive
capabilities.
Perform and interpret data studies and product experiments concerning new data
sources or new uses for existing data sources.
Develop prototypes, proof of concepts, algorithms, predictive models, and
custom analysis.
The average salary for a Data Scientist, IT is C$70,318 per year. Most people with this
job move on to other positions after 10 years in this career. The skills that increase
pay for this job the most are Big Data Analytics, Data Mining / Data Warehouse,
Machine Learning, Python, and R.
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Data Engineer
Data engineers typically work in an indoor office
setting, and a college degree in computer
science, engineering, or a related field is often a
minimum requirement for this position. Computer
skills, particularly with Linux systems, and three to
five years of prior work experience may also be required, and applicants should have
knowledge of algorithms, data structures, and performance optimism and experience
with processing and interpreting data sets.
Data engineers are responsible for developing and translating computer algorithms into
prototype code and maintaining, organizing, and identifying trends in large data sets.
Expected skills and experience also include proficiency in SQL database design,
proficiency in creating process documentation, strong written and verbal communication
skills, and the ability to work independently and on teams. Familiarity with the computer
coding languages python, java, kafka, hive, or storm may be required in order to
oversee real-time business metric aggregation, data warehousing and querying,
schema and data management, and related duties.
Data Engineer Tasks
Develop technical solutions to improve access to data and data usage.
Understand data needs and advise company on technological resources.
Aggregate and analyze various data sets to provide actionable insight.
Develop reports, dashboards, and tools for business-users.
A Data Engineer earns an average salary of C$81,556 per year. Most people with this
job move on to other positions after 10 years in this career.
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Data Modeler
A data modeler is a specialize analyst who takes
large chunks of data and attempts to pull useful
information out of it. The modeler then uses this
information to create detailed data reports for
businesses and clients. These reports outline the findings and provide actionable
analysis based upon macro and micro trends the modeler has discovered. A data
modeler's job is part information science and part statistical analysis. The modeler must
be sharp at both of these aspects of the position to succeed.
Data Modeler Tasks
Extract, evaluate, aggregate and analyze data from multiple databases to create
predictive and/or relational data models.
Conduct gap analyses and recommend ways to improve overall data quality,
metadata, and integration of data across systems.
Evaluate and document data quality and data cleansing efforts.
A Data Modeler earns an average salary of C$67,407 per year.
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Data Architect
Data architects are responsible for the design, structure, and
maintenance of data, usually organized in a relational database. A
data architect ensures the accuracy and accessibility of data
relevant to an organization or a project. The management and
organization of data is highly technical and requires advanced
skills with computers and proficiency with data-oriented computer
languages such as SQL and XML.
Data Architect Tasks
Create data architecture strategies for each subject area of the enterprise data
model.
Communicate plans, status and issues to higher management levels.
Create and maintain a corporate repository of all data architecture artifacts.
Collaborate with the business and other IT organizations to plan a data strategy.
Produce all project data architecture deliverables.
A Data Architect earns an average salary of C$100,935 per year. A skill in Database
Architecture is associated with high pay for this job. Experience has a moderate effect
on income for this job.
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Data Entry Specialist
A data entry specialist works on computers, entering information
for processing or records retention. In many cases, this work
may be repetitive, but accuracy is essential as this data is often
essential for the day-to-day operations of a company. Data entry specialists are needed
in a wide variety of environments, such as working with insurance information for
claimants and new applicants, updating product information for online retailers, and
processing patient records for large-scale medical facilities or clinics. Persons who work
in data entry normally work at a computer, entering and updating data in specialized
spreadsheets or proprietary forms/browsers. Due to the nature of the work, many
companies provide regular breaks for their data entry personnel, as complaints such as
tired eyes, headaches, and repetitive motion injuries in the hands and forearms are
frequent complaints of employees in this position.
Data Entry Specialist Tasks
Enter data into an information system.
Type rapidly and accurately both numerical and text data.
Inspect received data for possible errors.
The average wage for a Data Entry Specialist is C$14.87 per hour. Most people move
on to other jobs if they have more than 20 years' experience in this field. For the first five
to ten years in this position, wages increase somewhat, but any additional experience
does not have a big effect on pay.
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Data Visualization Specialist
Good understanding of visual art and design;
ability to turn statistical and computational
analysis into graphs, charts and animations;
ability to create new visualizations (e.g., motion charts, word maps) that draw insights
from the data and the analytics; and ability to generate static and dynamic visualizations
on a variety of visual media (e.g., reports, screens—from mobile screens to
laptop/desktop screens to high-definition large visualization “walls,” interactive
programs, to augmented reality glasses in the future).
Data Visualization Specialist Tasks
a. Provide value-add analysis to Business through use of visualization software to guide
analysis, drawing implications from analysis, and synthesizing into clear
communications.
b. Understand how data flows within various systems to provide input on requirements
for databases to ensure data is organized properly for reporting/analytics.
c. Work closely with Data Quality teams to ensure data integrity & completeness.
d. Develop business requirements to drive functional specifications for reporting
applications.
e. Work with business and cross-functional teams to thoroughly document reporting
processes and systems.
f. The acquisition, management, and documentation of data (including geo-spatial data).
g. Work with clients / client service teams to plan and carry out data analyses.
h. Participate in proposal writing, client deliverables and research papers.
i. Create visualizations from data / GIS data analysis for inclusion in proposals, reports,
papers and multi-media projects.
Data Visualization Specialist earns an average salary of $72,404 per year. Most people
with this job move on to other positions after 20 years in this field.
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Database Administrator (DBA)
A database administrator (DBA) is an IT
professional who ensures that the software used to
manage a database is properly maintained to allow
rapid access when needed. Because constant
access, searches, traffic are likely to have a damaging effect on any company
database, the DBA works to maintain the efficiency of the servers. He or she also will
typically work to ensure data security, coordinating with an IT security professional or
team in larger companies to help maintain the integrity of sensitive business data.
Database Administrator (DBA) Tasks
Implement, configure, and troubleshoot database instances, replication, backup,
partitions, storage, and access.
Set user privileges within the database environment.
Monitor and optimize system performance using index tuning, disk optimization,
and other methods.
Install, configure, troubleshoot, and maintain a database system.
A Database Administrator (DBA) earns an average salary of C$66,237 per year. Most
people move on to other jobs if they have more than 20 years' experience in this field.
Skills that are associated with high pay for this job are Oracle DB 8i/9i/10g/ 11i, Oracle,
and Linux.
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Database Developer
Database developers work in the IT department and are
responsible for the development and maintenance of
databases while following specific coding standards.
They will often analyze current database procedures in order to develop comprehensive
solutions to modernize, streamline and/or eliminate inefficient coding. This involves
monitoring, troubleshooting and debugging databases to solve performance issues.
Database developers also create ad-hoc scripts and cleanup scripts as needed. In
addition, they deliver written reports reviewing current coding and make
recommendations on changes that should be made to enhance performance. They also
often collaborate with other members of a development team in order to give and
receive feedback, and to develop the best solutions and procedures for the business.
The average pay for a Database Developer is C$63,634 per year. A skill in SQL Server
Integration Services (SSIS) is associated with high pay for this job. People in this job
generally don't have more than 20 years' experience.
Database Developer Tasks
Interact with client representatives and business analyst to develop database
solutions that meet business requirements.
Document work of operational responsibilities.
Support application of business intelligence and marketing automation solutions.
Support the database services in the design, delivery and operation of database
solutions.
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Data warehouse manager
Data warehouse managers oversee the storage of data in
facilities, analyzing this data as needed for departments
within their organization. They are primarily responsible for
evaluating data using metrics related to performance and usage, as well as analyzing
data load and monitoring job usage of data. The data warehouse manager is given
various data warehouse tasks by upper management, department chairs and other
parties within their organization; they must ensure data systems are fully functional to
ensure they can provide these stakeholders with necessary data.
Data Warehouse Manager Tasks
Design, implement, and oversee database management projects, making sure
projects stay on time and within budget.
Monitor databases to ensure they function properly and security protections are
up to date.
Provide information about the capabilities of database systems and help
employees learn how to use new systems or features.
Manage database administrators and other IT personnel in developing,
maintaining, and troubleshooting data storage systems.
The average pay for a Data Warehouse Manager is C$99,007 per year.
manager
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Data Warehouse Developer
Data warehouse Developers are computer engineers who
plan and build the data storage mechanisms within a
company, and they are primarily responsible for
developing a system that takes into account the needs and goals of the company so the
data warehouse suits those needs.
Data Warehouse Developer Tasks
Design, implement, and test the structure and schemas of the data warehouse.
Write stored procedures and code to implement extract, transform, and load
methodologies.
Design, implement, test, and debug database stored procedures and complex
queries to extract, calculate or manipulate information.
A Data Warehouse Developer earns an average salary of C$65,425 per year. Most
people with this job move on to other positions after 10 years in this field.
Developer
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ETL Developer
While designing data storage solutions for
organizations and overseeing the loading of data into
the systems, ETL developers have a wide range of
duties and tasks that they are responsible for. Below
is a list of the primary duties of an ETL Developer, as
found in current ETL Developer job listings.
Determine Data Storage Needs
The first task of the ETL Developer is to figure out the exact storage needs of the
company. They will need to have clear picture of the current data situation, and be able
to analyze different options to figure out the best fit.
Design and Create a Data Warehouse
Based on the determined needs, the ETL Developer then designs a data warehousing
system that meets the specific business needs, and works with a development team to
build the warehouse.
Extract, Transformation and Load of data
Once the warehousing system is developed, the ETL Developer extracts the necessary
data and transfers it to the new system.
Test and Troubleshoot
After the system is up and running, the ETL Developer must test their designs to ensure
the system runs smoothly. They fix any problems that may pop up.
Core skills
Based on ETL Developer job listings we looked at, employers are looking for
candidates with these core skills. Any prospective ETL Developer should have a strong
proficiency in these core skills before applying for the job.,
PL/SQL Oracle development experience
Hands-on experience with NoSQL databases
Experience pulling data from a variety of data source types
Dimensional modeling experience
Experience interfacing with business users and understanding their requirements
Ability to learn and implement new and different techniques
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Strong Project Management skills
Advanced skills
There are other skills that hiring managers would like an ideal candidate to have. These
are usually listed as preferred skills, and having them will improve your chances of
landing an ETL Developer job.
Experience with Hadoop Components – HDFS, Spark, Hbase, Hive, Sqoop
Experience with OLAP, SSAS and MDX
Java and/or .NET experience
Tools of the trade
The job of an ETL Developer is very technical, and requires the use of many specialized
tools to get the job done. Make sure you know how to use the following tools if you are
looking to apply for ETL Developer jobs.
Relational databases (SQL Server)
ETL tool sets, such as SSIS
Modeling tools such as Toad Data Modeler, Erwin and Embarcadero
.Net languages and Business Objects BI
A Senior ETL Developer earns an average salary of $86,250 per year.
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Business Intelligence (BI) Specialist
Business intelligence specialists are in charge of
assisting businesses with intelligence and information
technology solutions to improve operations and
overall profitability. These professionals help information technology professionals solve
request tickets and analyze a variety of metrics in different projects.
One of their main responsibilities is processing analytics using a variety of software
tools. This information is then read by other specialists. These specialists also write
detailed reports based on the business data found. In addition, these specialists share
important project data that can improve productivity and report their progress to the
business intelligence manager in their department. Some other responsibilities include
facilitating information gathering sessions and keeping accurate technical and business
documentation. These professionals manage and analyze data structure and quality on
a regular basis to make business decisions.
Business Intelligence Specialist Tasks
Provide application analysis and data modeling design to collect data for
centralized data warehouse.
Extract data from databases and data warehouses for reporting and to facilitate
sharing between multiple data systems.
Proficient in the use of query and reporting analysis tools.
Standardize data collection by developing methods for database design and
validation reports.