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10-11-2021, 01:38

Business Intelligence & Data Analytics Certification Course

Category: Tutorials

Business Intelligence & Data Analytics Certification Course
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 44 lectures (27h 51m) | Size: 4.55 GB




Learn and apply Business Intelligence and Analytics concepts to practical business problems. Become a BI / Data Analyst
What you'll learn:
Explain the concepts of Business Intelligence and Data Analytics
Leverage BI & analytics in finding solutions to business problems and improve performance
Learn different categories of BI - Mobile BI, Real time BI, etc.
Understand different types of analytics such as Data Analytics, Embedded Analytics, Collection Analytics, Survival Analytics, Geospatial Predictive Analytics
Describe the role of Machine Learning in BI
Learn & build Data Warehouses, Data Marts, Data Lakes, Data Platforms
Understand Predictive Modeling, Regression Models, Data Vault Modeling
Get introduced to NoSQL, NLP, Salesforce, Apache Server
Kickstart your career as a BI/Data Analyst or Business Consultant

Requirements
Enthusiasm and determination to make your mark on the world!

Description
Uplatz brings this detailed course on Business Intelligence & Data Analytics to help you get familiar with the concepts and application of business analysis, the tools & technologies involved in business analytics domain, and finally to get you skilled in applying the same to practical business scenarios.

If you wish to make a successful career in this super trending area of data analytics and business intelligence commanding huge pay packages, then this is perfectly the right course for you to get you started. Besides going into detail of understanding data and performing meaningful analytics on it, this Business Intelligence & Data Analytics course also introduces you briefly to the concepts of machine learning and data science.

Data gathering, storage, and knowledge management are combined with data analysis in business intelligence systems to evaluate and transform complex data into meaningful, actionable information that can be used to support more effective strategic, tactical, and operational insights and decision-making. An organization's business intelligence environments are made up of a number of technologies, applications, processes, strategies, products, and technological architectures that are used to gather, analyze, display, and disseminate internal and external business data.

The use of methodologies such as data mining, predictive analytics, and statistical analysis in order to analyze and transform data into useful information, identify and anticipate trends and outcomes, and ultimately make smarter, data-driven business decisions, is referred to as business intelligence and analytics, a data management solution and business intelligence subset.

A business intelligence platform allows companies to take use of their current data architecture and construct unique business intelligence apps that allow analysts to query and view data. Self-service analytics is supported by modern business intelligence solutions, making it simple for end users to build their own reports. Users may connect to a variety of data sources, including NoSQL databases, Hadoop systems, cloud platforms, and traditional data warehouses, using simple user interfaces mixed with flexible business intelligence backend software to produce a unified picture of their heterogeneous data.

Our Business Intelligence and Data Analytics course aims to produce a select group of skilled individuals who are cross-trained in business process analysis, technology management, and technically skilled in all aspects of data science, such as predictive modelling, analytical reporting, GIS mapping, segmentation analysis, and data visualization along with machine learning & deep learning. Students will acquire the skills to integrate cutting edge information and analytics technologies with best practices and applied business methods.

The Business Intelligence & Analytics course combines analytical and professional skills to help you become the type of manager who questions assumptions and makes evidence-based choices based on facts. You'll learn new skills that will help you improve your goods, services, and strategies while leading your firm through markets that are always changing due to technological advancements. Machine learning, language processing, data mining, data modeling including predictive modeling, optimization, NoSQL, NLP are among the topics covered in the curriculum, which are at the forefront of the data revolution. Classes go beyond the fundamentals of understanding data and using it for making business decisions, to addressing essential business ideas.

Business Intelligence & Data Analytics - course curriculum

Introduction to BI Concepts, Examples, and Applications

Introduction to Predictive Modeling

Introduction to NoSQL

Hierarchical Clustering

Introduction to Salesforce

Introduction to NLP

Introduction to Apache Server

Business Intelligence deep-dive

Data Warehousing

Types of Data

Mobile BI

Real-time BI

Data Analytics

Data Analytics vs. Business Analysis

Embedded Analytics

Collection Analytics

Survival Analytics

Machine Learning Techniques

Geospatial Predictive Analytics

Cohort Analysis

Data Mining

Anomaly Detection

Statistically Sound Associations

Cluster Analysis

DB Scan

Regression Models

Extraction-based Summarization

Machine Learning in BI

Machine Learning vs. BI

How ML can make BI better

Understanding Data Warehousing

Understanding Data Mart

Understanding Data Dimensions

Understanding Data Vault Modeling

Understanding Links and Satellites

Who this course is for
Business Intelligence Engineer
Data Analyst / Data Analytics Specialist
Business Analyst/Consultant
BI Analytics Professional
Business Intelligence Specialist
Data Engineer: Business Intelligence
Reporting & Analytics Analyst
Analytics Manager
Financial Analyst / Marketing Analyst / Operations Analyst
Data Science Analyst
Business Analytics Lead
Machine Learning Engineer
MIS / Reporting Analyst
BI Developer
Project Manager
Research Analyst


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