With 12 Topic Training Related to
Business Information & Data Management
Putar Video
- Modul 1 : Introduction to Data Management
- Modul 2 : Database Management Systems
- Modul 3 : Developing Data Management Strategy
- Modul 4 : Data Integration
- Modul 5 : Master Data Management
- Modul 6 : Data Governance
- Modul 7 : Challenges and risks to Data management
- Modul 8 : Data security and regulatory compliance
- Modul 9 : Innovation in Data Management
- Modul 10 : Data Management Best Practices and latest
trends
- Modul 1 : BIG DATA BATCH PROCESSING
- Modul 2 : DESIGN BIG DATA BATCH PROCESSING
SOLUTIONS - Modul 3 : BIG DATA REAL-TIME PROCESSING
SOLUTIONS - Modul 4 : DESIGN BIG DATA REAL-TIME PROCESSING
SOLUTIONS - Modul 5 : OPERATIONALISE END-TO-END CLOUD
ANALYTICS SOLUTIONS - Modul 6 : IMPLEMENTING DATA STORAGE IN AZURE
- Modul 7 : DATA FACTORIES AND WORKFLOWS
- Modul 8 : POWERSHELL FOR TECHNOLOGY
PROFESSIONALS - Modul 9 : OPERATIONALISE END-TO-END- CLOUD
ANALYTICS SOLUTION - Modul 10 : SCRIPTING
- Modul 11 : HDInsight
- Modul 12 : HOSTING SERVICES ON-PREMISES AND IN
AZURE
- Modul 1 : ESSENTIAL REPORTING REQUIREMENT SKILLS
- Modul 2 : BUILDING THE EXCEL DASHBOARD – LOOKUP
DATA - Modul 3 : BUILDING THE EXCEL DASHBOARD – FILTERING
DATA - Modul 4 : BUILDING THE EXCEL DASHBOARD – SUBTOTALS
- Modul 5 : BUILDING THE EXCEL DASHBOARD – PIVOT
TABLES ANDPIVOT CHARTS - Modul 6 : BUILDING THE EXCEL DASHBOARD –
INTERACTIVE BUTTONS - Modul 7 : BUILDING THE EXCEL DASHBOARD –
FORMATTING - Modul 8 : ADVANCED DATA STRUCTURING TECHNIQUES
- Modul 9 : CHARTING AND VISUALISATION TECHNIQUES
- Modul 10 : CHARTING AND VISUALISATION TECHNIQUES
- Modul 11 : MACRO CHARGED REPORTING
- Modul 1 : Data Science Overview
- Modul 2 : Statitical Analysis and Business Applications
- Modul 3 : Python Environment Setup and Assentials
- Modul 4 : Mathematical Computing with Python (NUMPY)
- Modul 5 : Scientific Computing with Python (SCIPY)
- Modul 6 : Data Manipulation with Pandas
- Modul 7 : External Barriers to Listening
- Modul 8 : Machine Learning with Scikit-Learn
- Modul 9 : Natural Language Processing with Scikit Learn
- Modul 10 : Data Visulization In Python Using Mat plot-LIBÂ
- Modul 11 : Data Visulization In Python Using Mat plot-LIB
- Modul 12 : Integration with Hadoop Map-Reduce and Spark
- Modul 1 : INTRODUCTION
- Modul 2 : CHARACTERISTICS OF DATA
- Modul 3 : DATA MODELS
- Modul 4 : DATA STREAMING
- Modul 5 : DBMS AND DATA MANAGEMENT
- Modul 6 : DATA OPTIMISATION
- Modul 7 : DATA SUPPORTING DECISION-MAKING
- Modul 8 : DECISION TREES
- Modul 9 : DESCRIPTIVE ANALYTICS
- Modul 10 : PREDICTIVE ANALYTICS
- Modul 11 : PRESCRIPTIVE ANALYTICS
Putar Video
- Modul 1 : BIG DATA
- Modul 2 : BIG DATA HANDS-ON PRACTICE EXERCISE
- Modul 3 : HADOOP
- Modul 4 : HADOOP EXERCISES
- Modul 5 : MAP REDUCE
- Modul 6 : YARN
- Modul 7 : Apache HIVE
- Modul 8 : Apache PIG
- Modul 9 : IMPALA
- Modul 10 : SQOOP
- Modul 11 : UBUNTU
- Modul 12 : CONFIGURATION MANAGEMENT
Putar Video
- Modul 1 : INTRODUCTION
- Modul 2 : CHARACTERISTICS OF DATA
- Modul 3 : DATA MODELS
- Modul 4 : DATA STREAMING
- Modul 5 : DBMS AND DATA MANAGEMENT
- Modul 6 : DATA OPTIMISATION
- Modul 7 : DATA SUPPORTING DECISION-MAKING
- Modul 8 : DECISION TREES
- Modul 9 : DESCRIPTIVE ANALYTICS
- Modul 10 : PREDICTIVE ANALYTICS
- Modul 11 : PRESCRIPTIVE ANALYTICS
- Modul 1 : What are infographics?
- Modul 2 : Planning layout for infographics
- Modul 3 : What makes infographics effective?
- Modul 4 : Selecting the appropriate infographic
- Modul 5 : Infographics designing process
- Modul 6 : Designing wireframe
- Modul 7 : Designing infographics
- Modul 8 : Use of Charts
- Modul 9 : Infographics and SEO
- Modul 10 : Infographics reporting
- Modul 1 : BASICS OF INSIGHT GENERATION
- Modul 2 : THE DIFFERENT DATA SCIENCE FIELDS
- Modul 3 : INTRODUCTION TO DATA AND DATA SCIENCE
- Modul 4 : COMMON DATA SCIENCE TECHNIQUES
- Modul 5 : COMMON DATA SCIENCE TOOLS
- Modul 6 : BASIC STATISTICS: FOUNDATIONS OF
QUANTITATIVE INSIGHTS - Modul 7 : THE NORMAL DISTRIBUTION AND HISTOGRAMS
- Modul 8 : MACHINE LEARNING WITH SCIKIT–LEARN
- Modul 9 : ADVANCED CHARTS AND DASHBOARDS
- Modul 10 : DEMAND FORECASTING
- Modul 1 : DATA ANALYSIS WITH EXCEL
- Modul 2 : PIVOT TABLES
- Modul 3 : USING PIVOT TABLES FOR ADVANCED
CALCULATIONS - Modul 4 : AGGREGATE DATA
- Modul 5 : LAB ENVIRONMENT & INSTALLATIONS
- Modul 6 : QUERIES
- Modul 7 : DATA FILTERS & MEASURES
- Modul 8 : DATA VISUALISATIONS
- Modul 9 : CASE STUDIES
Putar Video
- Modul 1 : Overview of Data Protection and Freedom
of Information - Modul 2 : Principles for Data Collection
- Modul 3 : Principles for Freedom of Information
- Modul 4 : Guidelines for Data Sharing
- Modul 5 : Data Sharing Arrangements in the Public Sector
- Modul 6 : General Data Protection Regulation (GDPR)
- Modul 7 : Challenges in Data Protection and Ways to
Overcome Them - Modul 8 : Challenges in Information Sharing and Ways to
Overcome Them
- Modul 1 : Why data visualization ?
- Modul 2 : Data Visualization Process
- Modul 3 : Use of Mapping
- Modul 4 : Use of Bar Graphs
- Modul 5 : Use of Pie Charts
- Modul 6 : Use of Histograms
- Modul 7 : Use of Line Graphs
- Modul 8 : Use of Scatter Plots
- Modul 9 : Challenges in Data Visualization
- Modul 10 : Current Trends
- Modul 11 : Excel Activity