So why it is important to know and learn about the different types of data format used in Excel.

 

What are those data format which we mostly get from our clients, and how we can get the clear view on data by just looking at its format.

 

Do you know that you can actually understand the data by just looking at its format and can proactively decide that what are the actions needed on data file.

 

Having knowledge about data formats like (.csv, tsv and .xlsx) can help you to make decisions for analysing data further. 

 

1.       Tab Separated Imports (. tsv ).

 

It’s a plain text format for storing tabular data, in which data is separated by Tab ( \ ) and are mostly text heavy data, more cleaner format as compared to .csv data files.

 

TSV stand for (tab separated value) and is denoted by ( .tsv ). We always need to put the ( .tsv ) at last of file name, ( .tsv ) denotes the format of the data file.

 

We Mostly get this data from the third party data base like CRMs, and online platforms.

 

File format identifier: - you can see ( .tsv ) at last of file name.

 

2.       Raw Tabular data.

 

It’s a raw tabular data which is unprocessed or a data which is unformatted and contains unorganized rows and columns data, missing values. This type of data needs heavy cleaning and processing to make it more valid for further analyzation.

 

We mostly get this data from client datasets like HR Data, financial transactions, and sales records.

 

This is a type of raw data which we mostly get from our clients, in ( .xls or .xlsx ) format.

 

File format identifier: - you can see ( .xls or .xlsx ) at last of file name.

 

3.       Power Query / Power Pivot.

 

Power Query is a tool which is used for data cleaning, data imports, and Data transformation whereas Power Pivot is an Excel’s engine used for creating connection between different datasets like data modelling and analysing. When both are combined can create a powerful data insight.

 

Sometimes we get data which are related to pivot tables and power query, the data consist of advance pivot tables/charts, power query files, interactive dashboards, data models.

 

We get these data from our clients for doing advanced data formations and modelling.

 

File format identifier: - you can see ( .xlsx ) at last of file name.

 

4.        Macros & VBA Script.

 

These types of data are not tables, charts, or graph, but actually consist of excel programming language known as VBA scripts which store instruction given in macro, and a macro is a set of instructions which records every click, keystrokes, formatting & changes you make while recording data.

 

Data are very large, complex, and complicated and are generally dash boarded and automated with stats, graphics, tables & chart.

 

We mostly get these types of data for visualising, repetitive task handling, and automated workflows.

 

File format identifier: - you can see ( .xlsm ) at last of file name.

 

5.       Form Templates.

 

These are basically tabular data formats which are collected from data entry, online forms, surveys, client questionnaires, and online response collected from users.

 

Form templates are structured blueprints of data collected in various formats like word, PDF, Excel, web, and XML files.

 

Datasets like these are mostly found in client reports or in tabular form.

 

File format identifier: - you can see ( .xlsx ) at last of file name.

 

6.       External data Connections.

 

When we get connected to external data resources like, databases, APIs, or file. The data can be arrived in different file formats like SQL, CSV, TSV, TXT, XLS/XLSX or Open Document Spreadsheet which is open source and known as ODS.

 

We need to convert file formats to run it on other platforms, which makes it compatible to run on other sources.

 

File format identifier: - you can see .docx, .PDF, .csv, and .XML at last of file name.

 

7.       Delimited Data.

 

Delimited data is a tabular structure data, stored in plain text, where special characters known as (delimiters) separate’s value.

 

You will find each row on new line, whereas column is separated by comma, tab, semicolon, and different marks.

 

File format identifier: - you can see .docx, .csv or .xlsx at last of file name.

 

8.       Data Validation Sheets.

 

Validation spreadsheets are structured worksheet which runs on applied rules and constraints. It is a quality control layer of tabular data which neglects typos and errors, wrong formats, and invalid entries.

 

This type of data follows a special set of rules and ensures that data is valid. Validation sheets ensures that data is accurate and dataset follows the commanded structure.

File format identifier: - you can see .xlsx, .xls, .csv, .tsv, .pdf, .sql . at last of file name.

 

9.       Comma separated imports ( .csv ).

 

Comma separated values means where data is delimited by comma ( , ) or pipes ( | ). A delimiter sets boundaries for data which makes data easy to clean and analyse.

 

CSV file is the most common and universal file format used globally.

 

Data values are separated by comma and are tabular in format, where comma separates value.

 

Csv formats are simple text, comma separated and provides quick data exchange.

 

File format identifier: - you can see ( .csv) at last of file name.

  

10.        Charts &Graphs.

 

Charts and Graphs are for visualising the data matric in a creative manner. Visualising data formats gives us the instant view of data. It is popular type of data format, where the data consist of different type of charts, table, graphs, and automated interactive dashboards with visualizing effects.

 

Data visualizing can be applied to any type of datasets which consist of different file formats like, XLSX, CSV / TSV, PDF, PPTX, HTML, JSON, etc.

File format identifier: - you can see ( .csv, .xlsx) at last of file name.

 

Conclusion

 

If you carry good knowledge about the Data and its formats, then you can easily figure out the type of data you are dealing with.

 

By knowing the data formats clearly, you can proactively figure out that what are actions needed on data.

 

A good knowledge of data and its format, which comes with experience, can make you able to solve half of your problem by just looking at the data format.