Fundamentals of Business Intelligence & Data Analytics World
What you'll learn
- Learn about typical BI Project Lifecycle
- Learn about end-to-end BI Architecture
- Learn about different career tracks in a BI Architecture
- Learn about different tools / technologies available in the industry that are used to specific layers of BI Architecture
- Students need to know absolutely nothing about BI or Analytics as the course assumes that the students are completely non-technical
This is an introductory course for freshers / beginners / non-technical folks who want to take a sneak peek into the working of a Business Intelligence project and understand different career options and associated responsibilities for the same. This course is about how a BI project is executed, what are the different layers of a BI architecture, and which career track one can choose to work on based on your areas of interest in a BI project. This course is not meant to be a exhaustive reference of each and every tool and technology available in the Business Intelligence field.
This is a fully diagram guided course and focused on BI architecture majorly. This course also lists some industry leading tools and technologies from different vendors that fit into different areas of a BI project.
The course has three major sections - BI Project Lifecycle, BI Architecture and BI Career Tracks. The course does not come with any practice tests or do-it-yourself kind of exercises. But if you have a career or technical question related to this course, I would be able to help the students with the same.
Who this course is for:
- Students who are non-technical and curious about how to start a career in Business Intelligence and Analytics should take this course
- Students who are taking their starting steps out of college in the field of Business Intelligence and Analytics should take this course
- Students who are from a different technical domain and wants to hear a 14-year experienced architect's advise to make a career in BI and Analytics should take this course
Udemy's Top 10% of most engaging instructors
My name is Siddharth Mehta. I have career experience of more than 15 years in the IT Industry and am presently working as Enterprise Cloud Architect. I am published author on many online and print-media publications. I have taught thousands of students on Udemy and have number of courses on Data and Analytics.
Would you consider learning from just any hobbyist who knows programming or someone who just teaches programming without practically using it in the real world, or someone who has experience of using the technology in real world on multi-million dollar large-scale projects globally ? I will teach you everything I know about the subject, from my years of practical experience in the field of BI, Data, Analytics, Cloud and Data Science.
If you are interested in learning more about me, below are some of my career highlights:
I have career experience of more than 15+ years and am presently working in New York Metro region as Enterprise Architect for a life-sciences proprietary multi-tenant product technology portfolio, managing an ecosystem of ISVs and tenants. Below are some of my career highlights:
-|- International experience of working across geographies (US, UK, Singapore) for multi-national clients in Banking, Logistics, Government, Media Entertainment, Products, Life Sciences and other domains
-|- Lead architecture of multi-million dollar portfolios containing apps in Cloud, web, mobile, BI, Analytics, Data warehousing, Reporting, Collaboration, CMS, NoSQL and other categories.
-|- Official inventor of a patented application
-|- Published author/reviewer of whitepapers for Microsoft MSDN Library, Manning publication, Packt publication and others.
-|- Certifications: AWS Certified Solution Architect, TOGAF 9, CITA-F, HCAHD and more
In my present role, I remain responsible for Estimations like AO, IO, SI, IC & Security, Architecture Design, Technology Stack selection, Infra design, 3rd party products evaluation and procurement, and Performance engineering. Hands-On Technology experience of below tech:
-|- OS: Win, Linux
-|- Cloud: GCP, Azure, AWS
-|- Databases: Neo4j, AWS Neptune, Redis, Memcached, MongoDB, Cassandra, HBase, SQL Server, MariaDB, Postgres, Aurora, MySQL, SSAS, AWS Redshift, Google BigQuery, Azure Data Lake, AWS RDS, DynamoDB, Athena, AWS Elasticache
-|- Big Data: Google DataProc, AWS EMR, Kafka, Spark, Hive, Oozie
-|- Search: AWS Elasticsearch
-|- Web: Node.JS, Angular, jQuery, REST APIs, React
-|- ESB/ETL: AWS Lambda, Step Functions, AWS Kinesis, AWS Glue, Mulesoft, SSIS, AWS Data pipeline
-|- Data Science: R , Python, GGPlot 2, Numpy, Seaborn, Pandas, Skikit-learn, Spark ML, Data Mining, Regression & Classification algorithms
-|- Reports / Dashboards : Tableau, Qlikview, SSRS, AWS Quicksight, D3