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Lesson Posted on 05/09/2017 IT Courses/Data Modeling IT Courses/ERWIN Autosys IT Courses/Data Warehouse

Data Modeling Training Video

Kriti C.

I have 12+ years of experience as a working professional and trainer. I have expertise in Analytics domain...

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Lesson Posted on 31/08/2017 IT Courses/Data Warehouse IT Courses/Data Modeling IT Courses/ETL

Datawarehouse: Bill Inmon Vs. Ralph Kimball

Kriti C.

I have 12+ years of experience as a working professional and trainer. I have expertise in Analytics domain...

In the data warehousing field, we often hear about discussions on where a person / organization's philosophy falls into Bill Inmon's camp or into Ralph Kimball's camp. We describe below the difference between the two.Bill Inmon's paradigm: Data warehouse is one part of the overall business intelligence... read more

In the data warehousing field, we often hear about discussions on where a person / organization's philosophy falls into Bill Inmon's camp or into Ralph Kimball's camp. We describe below the difference between the two.

Bill Inmon's paradigm: Data warehouse is one part of the overall business intelligence system. An enterprise has one data warehouse, and data marts source their information from the data warehouse. In the data warehouse, information is stored in 3rd normal form.

Ralph Kimball's paradigm: Data warehouse is the conglomerate of all data marts within the enterprise. Information is always stored in the dimensional model.

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Lesson Posted on 10/04/2017 Functional Training/Data Analytics IT Courses/Big Data IT Courses/Programming Languages/Python +6 IT Courses/R Programming IT Courses/Scala Training IT Courses/Hadoop IT Courses/Big Data/Big Data Testing IT Courses/Tableau IT Courses/Data Modeling less

Data Science Career Shift

Bestintown Analytics Private Limited

Best in Town Analytics is a leading Data Science training and consulting firm with a proven track record....

Program Objective: The objective of this well designed and structured training program is to provide thorough understanding of Analytics concepts. You will learn essential skills, tools and techniques required to kick start your career as a successful Analytics/Data Science professional who understands... read more

Program Objective:

The objective of this well designed and structured training program is to provide thorough understanding of Analytics concepts. You will learn essential skills, tools and techniques required to kick start your career as a successful Analytics/Data Science professional who understands how to connect the mathematical and statistical concepts, data base concepts, machine learning models and business scenarios using programming with R and Python. You will also understand the role of Big Data Analytics by learning about Hadoop, Spark and other big data components. Lastly, we focus on creating insightful and intuitive visualizations using Tableau and help you take an international certification to announce your presence in the job market.

Scope of the Program:

  • The training plan would cover pre-readings, classroom sessions, group work and assignments corresponding to each session. corresponding to each session.
  • Most sessions focus on applications of Data Science, Big Data in real world scenarios.
  • In depth learning of R , Python and Machine learning
  • Working on Live projects to get real time exposure

Who Can Attend:

This program is designed to suit both working professionals and students alike. It suits well for Professionals (Mid-Career) who seek a successful reskilling in Data Science and accelerated career growth. IT personnel, MBA and B.E/B Tech students who are curious about Data Science and intend to travel in that field will find this course the right fit.

Pre-Requisites:

Basic understanding of Statistics, analytical tools and Big Data Components

Key Topics Covered:

  • Mathematics
  • Statistics
  • Tableau
  • SQL
  • R
  • Python
  • Machine Learning (R & Python)
  • Hadoop
  • Spark,Scala & hive
  • International Certification Preparation

PDF

  • Bigdata Analytics
ENROLL NOW

Course Content:

Mathematics

  • Essential Algebra
  • Numerical Methods
  • Differentiation
  • Integration
  • Matrices

Statistics

  • Permutation and Combination
  • Probability
  • Functions and Graph
  • Discrete Distributions
  • Continuous Distributions
  • Normal Distribution
  • Descriptive Statistics
  • Sampling Theory
  • Testing of Hypothesis
  • Basic Tests and ANOVA

SQL

  • SQL Overview
  • SQL SELECT statements
  • Functions and expressions
  • SQL updating
  • Joins
  • SQL with multiple tables
  • Summarization
  • SQL: preparing for the real world

International Certification

  • Wiley Book Revision & mock Exams
  • Examination

Big Data

  • Big Data - What, Why & Where?
  • Big Data Technologies
  • Hadoop and MapReduce
  • Introduction to Spark
  • Spark vs Hadoop
  • What are RDD's? - RDD Partitions / Lineage
  • RDD Transformation and Actions
  • RDD- Persisting and Caching
  • Spark Context, SQL Context, Hive Context
  • Data frame API's, Dataset API's
  • AWS- RDS and EMR

Big Data

  • Hadoop Basics - Hive and HDFS
  • Spark using Scala (Data Structures, Collections, Conditional Statements, Case Class)
  • Data Import and Export- CSV files, XML, Oracle DB, MySQL DB data processing
  • SparkR and Pyspark

Tableau

  • Basic Introduction, Sets and Dates
  • Conditional Field, Parameters and Logical Statement
  • Tabular Calculation and Different Type of Graphs
  • Level of Details
  • Working with Multiple Files, Map Graphs and Dynamic Properties to Graphs
  • Advance Analysis and Context
  • Dashboards Story Board and Actions
  • Tableau Public and Live Connection Data
  • Dashboard Case Study

SCALA

  • Introduction to Scala
  • Creating a Scala Doc & Project
  • The Scala REPL
  • Classes
  • Immutable and Mutable Fields
  • Methods
  • Arguments
  • Objects
  • Companion Objects
  • Case Classes and Case Objects
  • Apply and Unapply
  • Synthetic Methods
  • Collections overview
  • Sequences and Sets
  • Options
  • Tuples and Maps
  • Higher Order Functions
  • For expressions
  • Pattern Matching
  • Handling Options, Failures & Futures

Python

  • Python Overview
  • Environment
  • Basic Syntax
  • Variable Type
  • Basic Operator
  • Decision Making
  • Loops
  • Numbers
  • Strings
  • Lists
  • Unpacking a Sequence into Separate Variable
  • Dictionary
  • Extracting a subset of a Collection

Python

  • Calculation with Collections
  • Manipulation of List and all Collections
  • Iterators and generators
  • Self-iterators
  • Iterating in reverse
  • Set theory
  • Skipping values
  • Tuples
  • Date and Time
  • Functions
  • Modules
  • Files I/O
  • Classes and Objects

R Programming

  • Introduction
  • Data Import / Export
  • Data Subsetting
  • Data Manipulation
  • Functions and Loops
  • Regression Models
  • Clustering
  • Decision Trees
  • Machine Learning Basics
  • Neural Networks
  • SVM
  • PCA & Factor Analysis
  • Deep Learning
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5 Tips For Improving Your Documentation Immediately.

iTech Analytic Solutions

"iTech Analytic Solutions" (iTAS) is ranked as No. 1 Analytic Training Center in Bangalore by ThinkVidya.com "iTech...

Tip 1) Quit it with the Passive Voice The passive voice is a plague on effective documentation. It reduces its clarity, its consistency, and the efficiency and tightness of the writing. The passive voice is writing in which the subject of the sentence denotes the recipient of the action rather than... read more

Tip 1) Quit it with the Passive Voice

The passive voice is a plague on effective documentation. It reduces its clarity, its consistency, and the efficiency and tightness of the writing. The passive voice is writing in which the subject of the sentence denotes the recipient of the action rather than the performer. For example, “the server was installed” represents the passive voice while “the technician installed the server” represents the active voice. The passive voice is more common in most documentation because it is an easier, sloppier way of writing.

Writing in the passive voice is highly detrimental to documentation, especially to process related documentation where it is essential to understand which people or systems are performing the actions. The good news is that this is an easy fix. Under your Grammar function in Word, you can click on the “Passive Sentences” option and Word will automatically check for passive sentences for you.

To improve your documentation immediately: Use the Passive Voice grammar check function in Word to review your documentation and to change passive sentences into clearer, sharper active sentences.

Tip 2) Use Simple Visuals to Engage your Reader

You might not be a graphic artist, but you can improve your documentation quickly through using simple visuals. Take advantage of the many canned Shapes and Smart Art in Word to add a little “punch” to your documentation to better engage your audience.

If you have Microsoft Visio, then take advantage of the many ways that this program offers to draw simple diagrams which reduce your need for extensive text and which improve your chances of stakeholder engagement. One diagram that is particularly useful is the swim lane diagram which illustrates actors and their actions. Without being a process expert, you will be surprised how the simple Swim Lane will improve clarity in roles, responsibilities, and processes for your team and your organization overall.

To improve your documentation immediately: Create visuals in your documentation to illustrate your key messages, replace blocks of text, and to hold your readers’ attention.

Tip 3) Use Great Titles and Bullets

Remember, your audience generally wants to exert as little as energy as possible when reading your work. They’ll just “skim” your document looking for the main points. So, make things easy for them! Headers and bullets, often combined with effective visuals, are as important as the text. For some readers, headers and bullets are all that they will read.  Your reader might even make a decision about your work just by reading the table of contents. So, when assessing your documentation, it’s helpful if the entire gist of your work is communicated by the headers and bullets alone. Does the reader understand what you are trying to say? If they can understand most of what you are saying just by reading the headers, then you have done a good job.

To improve your documentation immediately: Revise your headers and bullets to summarize the whole document.

Tip 4) Tame your Acronyms and Buzz Words

There is perhaps nothing more annoying when it comes to documentation than walking onto a project or into a new organization and to be unable to understand a single paragraph in the document, because it is so full of acronyms and buzz words. Acronyms and buzz words do not, let me repeat, make you sound smarter. In most cases, they actually annoy your reader through hindering her ability to grasp your key messages.

Avoid using excessive acronyms and buzz words whenever possible. Or at least, define them upfront. In many cases, you should define acronyms and frequently used words in a well thought-out Glossary at the beginning of your documents or as part of your documentation library.

To improve your documentation immediately: Learn to tame your use of excessive acronyms and buzz words. If you need to use them, then make sure that you define them upfront at the beginning of your documents or documentation library.

Tip 5) Use the Reperformance Standard

One of the key challenges that organizations face in developing and maintaining excellent documentation is that they do not have a consistent standard for assessing their documentation. In reality, there are many different types of and uses for documentation and using one consistent standard is difficult. There is however one standard that provides a strong metric for most documentation. This standard is called the “reperformance standard”.

The reperformance standard states that the documentation must enable a user to “reperform” the related task or process. That is, the documentation must have sufficient detail and communicate with enough clarity through its text or visuals as a standalone document to allow the user to execute the steps. Although more commonly used by assurance and audit professionals, the reperformance standard can be expanded to many other applications within organizations, including training materials, user manuals, process documentation, and disaster recovery documentation. So, test the quality of your documentation against this standard and challenge yourself to ensure that you are meeting it.

To improve your documentation immediately: Review your document and ask: can someone else reperform these tasks based on what is written here?  If the answer is no – revise it so they can.

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10 Best Job Interview Tips for Jobseekers

iTech Analytic Solutions

"iTech Analytic Solutions" (iTAS) is ranked as No. 1 Analytic Training Center in Bangalore by ThinkVidya.com "iTech...

10 Best Job Interview Tips for Jobseekers:- 1. Conduct Research on the Employer, Hiring Manager, and Job Opportunity2. Review Common Interview Questions and Prepare Your Responses3. Dress for Success4. Arrive on Time, Relaxed and Prepared for the Interview5. Make Good First Impressions6. Be Authentic,... read more

10 Best Job Interview Tips for Jobseekers:-

1. Conduct Research on the Employer, Hiring Manager, and Job Opportunity
2. Review Common Interview Questions and Prepare Your Responses
3. Dress for Success
4. Arrive on Time, Relaxed and Prepared for the Interview
5. Make Good First Impressions
6. Be Authentic, Upbeat, Focused, Confident, Candid, and Concise
7. Remember the Importance of Body Language
8. Ask Insightful Questions.
9. Sell Yourself and then Close the Deal
10. Thank Interviewer(s) in Person, by Email, or Postal Mail.

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Microsoft Word

iTech Analytic Solutions

"iTech Analytic Solutions" (iTAS) is ranked as No. 1 Analytic Training Center in Bangalore by ThinkVidya.com "iTech...

Microsoft Word is a widely used commercial word processor designed by Microsoft. Microsoft Word is a component of the Microsoft Office suite of productivity software, but can also be purchased as a stand-alone product. It was initially launched in 1983 and has since been revised numerous times. Microsoft... read more

Microsoft Word is a widely used commercial word processor designed by Microsoft. Microsoft Word is a component of the Microsoft Office suite of productivity software, but can also be purchased as a stand-alone product.

It was initially launched in 1983 and has since been revised numerous times. Microsoft Word is available on both Windows and Macintosh operating systems.

Microsoft Word is often called simply Word or MS Word.

In 1981, Microsoft hired Charles Simonyi to develop a word-processing application. The first version was released in 1983. It was not initially popular, owing to its radically different look compared to WordPerfect, the leading word processor at that time. However, Microsoft improved Word continually over the years, including a 1985 version that could run on a Mac. The second major release of Word, in 1987, included an upgrade of major features in addition to new functionalities such as support for the rich text format (RTF).

In 1995, with the release of Windows 95 and Office 95, which offered a bundled set of office productivity software, sales of Microsoft Word increased significantly.
Microsoft Word offers several features to ease document creation and editing, including:

  • WYSIWYG (what-you-see-is-what-you-get) display: It ensures that everything you see on screen will appear the same way when printed or moved to another format or program.
  • Spell check: Word comes with an built-in dictionary for spell checking; misspelled words are marked with a red squiggly underline. Sometimes, Word auto-corrects an obviously misspelled word or phrase.
  • Text-level features such as bold, underline, italic and strike-through
  • Page-level features such as indentation, paragraphing and justification
  • External support: Word is compatible with many other programs, the most common being the other members of the Office suite.

The default file format was .doc prior to the Microsoft Word 2007 version; in 2007, .docx became the default file format.

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What is the difference between Analytics and analysis?

iTech Analytic Solutions

"iTech Analytic Solutions" (iTAS) is ranked as No. 1 Analytic Training Center in Bangalore by ThinkVidya.com "iTech...

Analysis> Separation of a whole into its component parts> Looks backwards over time, providing marketers with a historical view of what has happened Analytics > Defines the science behind the analysis. The science means understanding the cognitive processes an analyst uses to understand problems... read more

Analysis
> Separation of a whole into its component parts
> Looks backwards over time, providing marketers with a historical view of what has happened

Analytics
> Defines the science behind the analysis. The science means understanding the cognitive processes an analyst uses to understand problems and explore data in meaningful ways
> Method of logical analysis
> Look forward to model the future or predict a result
> Analytics also include data extract, transform, and load; specific tools, techniques, and methods; and how to successfully communicate results.

Analysis and analytics is to think in terms of past and future. Analysis. Data analytics is a broader term and includes data analysis as necessary subcomponent

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What is a Dashboard?

iTech Analytic Solutions

"iTech Analytic Solutions" (iTAS) is ranked as No. 1 Analytic Training Center in Bangalore by ThinkVidya.com "iTech...

Introduction There are many different ideas of what a dashboard is. This article will clearly define it along with other presentation tools. In article, What is BI? - A Business Intelligence Primer, it is discussed the presentation layer of the business intelligence technology stack. To reiterate, there... read more

Introduction

There are many different ideas of what a dashboard is. This article will clearly define it along with other presentation tools. In article, What is BI? - A Business Intelligence Primer, it is discussed the presentation layer of the business intelligence technology stack. To reiterate, there are typically four types of presentation media: dashboards, visual analysis tools, scorecards, and reports. These are all visual representations of data that help people identify correlations, trends, outliers (anomalies), patterns, and business conditions. However, they all have their own unique attributes.

Dashboards

Dashboard Insight uses Stephen Few’s definition of a dashboard:

A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.

Here are the key characteristics of a dashboard:

  • All the visualizations fit on a single computer screen — scrolling to see more violates the definition of a dashboard.
  • It shows the most important performance indicators / performance measures to be monitored.
  • Interactivity such as filtering and drill-down can be used in a dashboard; however, those types of actions should not be required to see which performance indicators are under performing.
  • It is not designed exclusively for executives but rather should be used by the general workforce as effective dashboards are easy to understand and use.
  • The displayed data automatically updated without any assistance from the user. The frequency of the update will vary by organization and by purpose. The most effective dashboards have data updated at least on a daily basis.



Visual Analysis Tools

Some consider tools that offer the ability to select various date ranges, pick different products, or drill down to more detailed data to be dashboards. At Dashboard Insight, we classify these as visual analysis tools.
Here are the key characteristics of a visual analysis tool:

  • It fits on one screen, but there may be scroll bars for tables with too many rows or charts with too many data points.
  • It is highly interactive and usually provides functionality like filtering and drill downs.
  • It is primarily used to find correlations, trends, outliers (anomalies), patterns, and business conditions in data.
  • The data used in a visual analysis tool is generally historical data. However, there are some cases where real-time data is analyzed.
  • It helps to identify performance indicators for use in dashboards.
  • It is typically relied on by technically savvy users like data analysts and researchers.



Scorecards

Scorecards and dashboards are often used interchangeably, but Dashboard Insight has a specific definition:

A scorecard is a tabular visualization of measures and their respective targets with visual indicators to see how each measure is performing against their targets at a glance

In addition, it should not be confused with Kaplan and Norton’s Balanced Scorecard. Here are the key characteristics of a scorecard:

  • It contains at least a measure, its value, its target, and a visual indication of the status (e.g. a circular traffic light that is green for good, yellow for warning, and red for bad) on each row.
  • It can be used in a dashboard but the scorecard should not be interactive nor contain scroll bars.
  • It can be used in a visual analysis tool but the scorecard doesn’t need to be interactive.
  • It may contain columns that show trends in sparklines.



Reports

Reports contain detailed data in a tabular format and typically display numbers and text only, but they can use visualizations to highlight key data.
Here are the key characteristics of a report

  • It presents numbers and text in a table.
  • It can contain visualizations but only used to highlight findings in the data.
  • It is optimized for printing and exporting to a digital document format such as Word or PDF.
  • It is geared towards people who prefer to read data, for example,  lawyers, who would rather read text over interpreting visualizations, and accountants, who are comfortable working with raw numbers.
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SQL Join Types

iTech Analytic Solutions

"iTech Analytic Solutions" (iTAS) is ranked as No. 1 Analytic Training Center in Bangalore by ThinkVidya.com "iTech...

There are four basic types of SQL joins: inner, left, right, and full. The easiest and most intuitive way to explain the difference between these four types is by using a Venn diagram, which shows all possible logical relations between data sets. 1. Inner Join2. Left Join3. Right Join4. Full Join read more

There are four basic types of SQL joins: inner, left, right, and full. The easiest and most intuitive way to explain the difference between these four types is by using a Venn diagram, which shows all possible logical relations between data sets. 

1. Inner Join
2. Left Join
3. Right Join
4. Full Join

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What is Hyperion?

iTech Analytic Solutions

"iTech Analytic Solutions" (iTAS) is ranked as No. 1 Analytic Training Center in Bangalore by ThinkVidya.com "iTech...

- Its an Business Intelligence tools. Like Brio which was an independent product bought over my Hyperion has converted this product name to Hyperion Intelligence. Is it an OLAP tool? - Yes. You can analyse data schemas using this tools. OLAP: Its an online analytical processing tool. There are various... read more

- Its an Business Intelligence tools. Like Brio which was an independent product bought over my Hyperion has converted this product name to Hyperion Intelligence.

Is it an OLAP tool?

- Yes. You can analyse data schemas using this tools.

OLAP: Its an online analytical processing tool. There are various products available for data analysis.

ETL: Extract , Transform and Load. This is a product to extract the data from multiple/single source transform the data and load it into a a table,flatfile or simply a target.

There is a quite a bit compitation in the market with regard to the ETL product as well as the OLAP products. These tools would definately be widely used for data load and data analysis purpose. 

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