career in data science - xcelvations€¦ · career in data science get ready for next revolution....
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Career in Data ScienceGet ready for next revolution
Data Science
Machine Learning
Artificial Intelligence
Data science includes Machine Learning and AI
A non-natural system who can do any
meaningful work that requires a decision
making
Any system other than natural ones, who can
learn and improve their decision on their own
Application of machine learning on data to
achieve your goals and objectives it is data
science
Open for experts of all domains
• Mathematics and Statistics
• Computer Science & Engineering
• Data Science
• Economics and Social sciences
• Natural Science
Data Science Jobs
Data Science Jobs
• Data Scientist
• Data Analyst
• Data Architect
• Data (Mining) Engineer
Related Jobs
• Business Intelligence Analyst
• Business Intelligence Developer
• Web and UI Developer for ML
• Cloud Engineer for ML
Data Mining Engineer
Data Architect
Data Analyst
Data Scientist
Data in context of Business Goals and Problems
Data Scientist
Data Analytics and ReportingData Analyst
Data MiningEngineer
Data Architect Analyse, integrate, centralize and maintain all data
Manage Database systemsGathering and pre-processing data
Data Scientist
• Discover a hidden insights with the unknown aspects of data
• There is no specific hypothesis
• Go through large amounts of data both structured and unstructured.
• Overall strategy of handling data and using it for business goals
• Pick right and important problems to analyze and address
• Many overlapping skills• Business domain understanding
• Big data systems like Hadoop, Spark
• ML/data processing programming skills like Python/R
• Database Engineering and ETL tools
• Statistics / data mining
Translate a business case into an
analytics agenda,
Develop hypotheses
Understanding Data
Develop impact measurements
metrics
Find, clean, and organize data
Develop models
Measure performance and
impactDeploy models
What is role of a data scientist?
Senior Data Scientist
• Business goal oriented to resolve highly complex business problems
• Be aligned with current needs but must anticipate for future needs and develop strategies and vision to meet those needs
• Innovative in using statistical data and developing new tools to develop analyze data.
Data Analyst
• Focused on a set of data identified by a data scientist or top management
• Transform and manipulate large data sets to suit the desired analysis for companies.
• Compilation and analysis of data to get analytical insights
• Convert data into reports to meaning business and visualization
Get hypothesis of business
goal or issue
Get/gather data for
processing
Understanding Data
Find, clean, and organize
data
Develop analytics and
modelsGet insights
Reports and visualization
What is role of a data analyst?
Data Architect
• Analyse, integrate, centralize and maintain all data
• Work closely with other stakeholders and data providers
• Secure data and control its access
• Improve data quality and eliminate redundancies
Data (Mining) Engineer
• Manages database systems (database administrators)
• Expert in database systems, SQL, ETL tools and Big Data
• Source data internally and externally
• Preprocesses, aggregates and segregates data and makes it meaningful and usable
• Providing real time data streams and batch data to analysts and data scientists
Business Intelligence Analyst
• Analyze internal and external business trends
• Discover insight into past data for meaningful reporting
Business Intelligence vs Data Analysts
BI Analyst
• Interprets past data to facilitate the end-users’ understanding
• Reporting or post-facto (descriptive) analytics
Data Analyst
• analyzes the past data to make future predictions
• Predictive or Prescriptive Analytics
Business Intelligence Developer
• Analyze past data and develop meaningful reports
• Use visualization to facilitate improved end-users’ understanding
Technologies (Our Expertise Only)
• Programming: • Python / R • SQL • Java
• Classical Machine Learning• Scikit-learn• NLTK
• Deep Learning• Keras/TensorFlow• PyTorch
• GUI Tools• Weka, Orange, Knime
• Data Visualization: • Tableau • D3.js • Python / Java / R libraries
• Big data platforms: • AWS• MongoDB • Microsoft Azure
• Other tools• Excel for data science
Career Transition
Domain experts without programming skillsBecome a Data Analyst
Data science is not just about programming, it is only a part of it
You will be most suited to get best of out of data
Data science is changing the world.
You often wonder!
You are not a programmer in the IT world.
Is it for you?
Now, GUI tools have evolved a lot
• GUI tools are intuitive
• They cover wide range of business needs
• They allow you to concentrate on solution to business needs
• Your business intelligence will get best out of these tools
• Many major GUI tools and platforms are available
• Microsoft Azure
• IBM Watson
• Amazon AWS
• SAS
• Weka
• and many more…
Domain experts advantage
• You understand more about data and business needs
• You can discover hidden insights better than others
• Learning a tool is easier than getting domain expertise
• Visualization ideas will come naturally to you
A domain expert
Start with GUI tools
Learn Jupyter Notebook
Data Visualization
Learn working with ML in Cloud
Progression in ML for domain experts
UI designers and Microservices DevelopersBecome Web and UI Developer or Cloud Engineer for ML/Data Science
Leverage your visualization and creativity to gain upper hand
Work with ML/Data Science in cloud
Data Science for Web Developer and UI Designers
• Microservices & UI• Develop end points for ML systems and trained models
• Develop end point for data streaming and processing
• Cloud• Manage and deploy trained models
• Develop and deploy web/mobile apps for end users
• Visualizations• Impactful presentation of data visualization
Data Science for Web Developer and UI Designers
ML Models, Systems and Data Sources
Microservices for data and ML
models
Web and mobile apps for end users of ML
Cloud deployments
Impactful presentation of
data visualization
R/Python/Java ProgrammersBecome a Data Analyst
You have already got advantage
Data Science for R/Python/Java Programmers
• You already have an advantage
• Get started with basic concepts of machine learning
• Start working with classical ML and progress to deep learning
• Learn data visualization tools like Tableau
• Learn how to work with ML in cloud
Data Science for R/Python/Java Programmers
Python/R/Java
Learn basic ML
concepts
Classic ML
Deep Learning
Visualization
ML in Cloud
Database Admins and DevelopersBecome a Data Architect / Data Engineer
Data is natural to you. Deep learning needs lot of data and you know how to get it
Data Science for Database Admins and Developers
• Get started with basic concepts of machine learning
• Progress to deep learning – learn how to use you database skills to your advantage
• Focus on making data relevant, meaningful, non-redundant
• Master pre-processing and data-streaming for ML/Data Science
• Learn use of SQL, ETL tools and Big Data in ML/Data Science
• Learn data security and control issues with ML in cloud
• Data visualization will be logical progression to your skill-set
Data Science for R/Python/Java Programmers
Database Admins
and Developers
Learn basic ML
concepts
Deep Learning
Data Pre-processing
Data Security and Streaming
Visualization
ERP ProfessionalsSAP, Oracle ERP etc
Become a Data Analyst
Data Science for ERP Professionals
• Concentrate on business issues and goals
• Learn classic machine learning and deep learning
• Use GUI tools to speed up learning
• Focus on data visualization in most meaningful way
• Learn how to integrate your ERP modules with ML models and solutions
• Learn how to work with cloud and your ERP modules
Data Science for R/Python/Java Programmers
ERP Professionals
Learn ML concepts
Deep Learning
Data Visualization
Integration of ERP and ML/Data Science
Cloud and you ERP
Thank You