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Turning Spreadsheets into Corporate Data

  • Course Code: Data Analysis / BI - Turning Spreadsheets into Corporate Data
  • Course Dates: Contact us to schedule.
  • Course Category: Big Data & Data Science Duration: 4 Days Audience: This course is geared for Python experienced developers, analysts or others who wants to Master the spreadsheet disambiguation technique and create credible and well-organized spreadsheets

Course Snapshot 

  • Duration: 4 days 
  • Skill-level: Foundation-level Spreadsheets skills for Intermediate skilled team members. This is not a basic class. 
  • Targeted Audience: This course is geared for Python experienced developers, analysts or others who wants to Master the spreadsheet disambiguation technique and create credible and well-organized spreadsheets  
  • Hands-on Learning: This course is approximately 50% hands-on lab to 50% lecture ratio, combining engaging lecture, demos, group activities and discussions with machine-based student labs and exercises. Student machines are required. 
  • Delivery Format: This course is available for onsite private classroom presentation, or remote instructor led delivery, or CBT/WBT (by request). 
  • Customizable: This course may be tailored to target your specific training skills objectives, tools of choice and learning goals. 

Spreadsheets are a popular way to store and communicate business data, but, although they are easy to create and update, they are not reliable enough to be used for making important corporate decisions. With this course, you can gain insight into how to maintain spreadsheets, how to format them, and then convert them into a database of reliable and useful information. Turning Spreadsheets into Corporate Data starts with a quick history of spreadsheet usage. You’ll learn the basics of formatting spreadsheets, including how to handle special characters and column headings, and how to convert the spreadsheet first into an intermediate database and then into corporate data. You will also learn how to utilize the mnemonic dictionary that is created along with the intermediate database. The later chapters discuss the immutability of data and the importance of organizational and political considerations during the data transformation. By the end of this course, you’ll have the skills and knowledge needed to convert your spreadsheets into reliable corporate data. 

Working in a hands-on learning environment, led by our Spreadsheets expert instructor, students will learn about and explore: 

  • Gain insight into the different factors that affect the transformation of spreadsheets into data 
  • Explore in detail the basics of spreadsheet formatting 
  • Discover ways to handle non-standard spreadsheet structures 

Topics Covered: This is a high-level list of topics covered in this course. Please see the detailed Agenda below 

  • Study the two ways of viewing spreadsheets: internal and external 
  • Establish guidelines for the end-user while submitting spreadsheets 
  • Discover ways to compensate for the shortcomings of the .pdf formatting 
  • Learn how to convert intermediate data from spreadsheets into corporate data 
  • Work with the mnemonic dictionary 
  • Understand data modeling through the entity-relationship diagram 

Audience & Pre-Requisites 

This course is geared for attendees with Python skills who wish to Master the spreadsheet disambiguation technique and create credible and well-organized spreadsheets 

Pre-Requisites:  Students should have  

  • developers with some knowledge of Python.  

Course Agenda / Topics 

  1. Brief History of Spreadsheets 
  • The IT Labyrinth 
  • End User Acceptance of the Spreadsheet 
  • Spreadsheet Hell 
  • A Tradeoff 
  • Responsibility—The Flip Side of Control 
  • Management’s Problem 
  • Differences Between Two Types of Data 
  1. Spreadsheet Paradox 
  • Public Data 
  • The Spreadsheet as a Medium of Exchange 
  • Recurring/Non-Recurring Spreadsheets 
  • The Spectrum of Spreadsheets 
  • The Cost of Transforming a Spreadsheet 
  • Factors Other than Cost 
  • Transcription of Data 
  • Cell Formula 
  • Spreadsheet Descriptors 
  • Artificially Supplying Descriptors 
  1. Spreadsheet Varieties 
  • Simple Demarcation—xlstab 
  • Other Special Characters—eold and Linefeed 
  • The Internal View of a Spreadsheet 
  • A Missing Column Heading 
  • A Missing Value 
  • A Multiline Row 
  • The “Standard” Spreadsheet Format 
  • Managing the User of the Spreadsheet 
  • The ssdef Table 
  • The Spreadsheet Processing Log 
  • The Lineage of Spreadsheet Data 
  • The Cell Formula 
  • Relating to the Real World 
  • Identifying the Header Line 
  1. The PDF Spreadsheet 
  • The Importance of Special Characters 
  • PDF and OCR 
  • A Final Option 
  1. The Basics of Spreadsheet Formatting 
  • The System Name 
  • Unreliability of Report Name 
  • Multiple Sheets in a Spreadsheet 
  • Other Special Characters 
  • Identifying Column Headings 
  • Similar Column Headings 
  • Blocking Off Sections of a Spreadsheet 
  • Non-Standard Spreadsheet Structures 
  • A Spreadsheet that Cannot be Mapped 
  • A Spreadsheet in a TXT Format 
  1. Spreadsheet Disambiguation 
  • Selecting Spreadsheets for Inclusion into Corporate Data 
  • Recasting the Spreadsheet 
  • Logging the Spreadsheet for Transformation 
  • Entry into the Path Queue 
  • Defining the Spreadsheet Headings 
  • Pairing the ssdef Specification to the Spreadsheet 
  • Finding and Creating Database Definitions and Values 
  • The Intermediate Database 
  • Some Anomalies 
  • What if an Error is Discovered? 
  • Manual Effort Required 
  • Spreadsheet Width 
  • Subdividing a Spreadsheet 
  • No Value for a Column Name 
  • No Column Headings 
  • Creating the ssdef Specification Once 
  1. The Intermediate Database 
  • Finding Errors 
  • The Contents of the Intermediate Database 
  • Functions Served by the Data Elements 
  • Alternate Name 
  • Adding Context to Data Values 
  • Editing Data in the Intermediate Database 
  1. The ssdef Database 
  • Organizing Data Inside the ssdef Table 
  • Processing Using ssdef Records 
  • Searching the Full Path Queue 
  1. The Corporate Database 
  • From Intermediate Data to Corporate Data 
  • Grouped Corporate Data 
  • Tracing the Lineage 
  1. The Mnemonic Dictionary 
  • The Contents of the Mnemonic Dictionary 
  • Grouping Like Data Elements 
  • Applying Naming Conventions 
  • Value of the Mnemonic Dictionary 
  1. Political Considerations Within the Organization 
  • Shifting Control 
  • Immutability of Data 
  • The Importance of Alternate Names 
  • Limited Editing 
  • Super Classifications of Data 
  • The Lineage of Corporate Data 
  • Relative Volumes of Data 
  1. Data Modeling and the Spreadsheet Environment 
  • The Entity Relationship Diagram 
  • The Data Item Set 
  • The Physical Model 
  • The Data Model 
  • The Data Model and Spreadsheet Data 
  • “Correctness” of Data 
  • Aligning Data from Different Spreadsheets 
  • An Algorithmic Resolution 
  • An Indexed Resolution 
  • Resolution and the Data Model 
  • Spreadsheet Data in the Data Warehouse 
  • Changing Spreadsheet Data 
  1. Case Study 
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