The term data has been around for a very long time. However, only a small percentage of the population is aware of the precise nature of data and its potential to alter the course of history. In an epoch where 2.5 quintillion bytes of data are produced every day, data is essential for many things such as decision-making for business operations. Analytics are now not just used by large, wealthy corporations. In fact, research has shown that nearly 60% of businesses employ analytics in some way and it is already widely used. Needless to say, businesses are making use of this technology in a variety of ways.
All that said, data can only be effective if it is managed competently with the appropriate tools. Data, being one of the most precious assets of any business, has the potential to have a substantial impact on its long-term prosperity. In order to adequately utilize all available data and make it as precise as possible, it’s imperative to use the appropriate tools and technology. Two of the most common and effective methods for working with data are Excel and SQL and the Excel vs SQL battle has always been a topic of debate. But what exactly are these data-related tools? Which one is better, and which one should you learn?
Also read: Top Data Science Applications
WHAT IS EXCEL?
One of the most widely used data analysis programs is Microsoft Excel, with the built-in pivot tables being the most widely used analytical tool. Microsoft Excel is a computer program that leverages spreadsheets to assist users in storing, modifying, and analyzing data. Data can be examined and interpreted in a variety of ways using Microsoft Excel. Excel stores data points in each cell in its most basic form. For better viewing and categorization, everything including raw data exports, sale dates, SKUs, or the number of units sold is recorded (or imported) into a spreadsheet. An effective Excel spreadsheet will arrange unstructured data into a legible format that makes it simpler to glean insights that can be put to use. Additionally, excel lets users modify fields and functions that perform computations when dealing with more complicated data. Segmented data can be examined more thoroughly and visualised without the aid of additional tools, even for larger data sets. Even though it cannot create a full-scale data product on its own, Excel can nevertheless display clear visualisations and precise calculations. Before jumping to the conclusion that Excel is the winner in the Excel vs SQL battle, let us look at a few advantages and disadvantages of Excel.
EXCEL: PROS AND CONS
|Simplifies data||Large number of features that are not intuitive for beginners.|
|More visuals||Only available on Windows and Mac OS X, which poses a problem for users of Linux and other operating systems.|
|Orderly, logical and easier data organization||Susceptible to trivial human errors|
|Better formula and calculation features||Incapable to manage large datasets.|
|Third-party support||Spreadsheet Sprawl and Security Risk|
WHAT IS SQL
Structured Query Language is referred to as SQL. To manage big databases and extract pertinent data for business purposes, data analysts use SQL. A general-purpose programming language is not SQL. SQL does not allow users to write complex programs like Python or Java; instead, it primarily will enable one to read, search, and alter databases to organize and tabulate raw data. The leading database technology is relational database management systems (RDBMS). SQL is used by almost all varieties of RDBMS. Listed below are a few of the pros and cons of SQL to help you choose a winner in the Excel vs SQL battle?
Also read: How Crucial is SQL for Data Science?
SQL: PROS AND CONS
|Handles large volumes of data.||Pricing of premium packages|
|Supreme security, backup, and auditing features||Poor Interface|
|Simple to learn||Doesn’t grant complete control over databases|
|Faster Query Processing||Less accessible than Excel.|
|Standard Language||Substantial time must be spent in planning before the database is ever brought into production as SQL database’s schema must be defined before use.|
EXCEL vs SQL; WHO WINS?
The final verdict of the battle Excel vs SQL depends entirely on just how much data users have and what they intend to do with it. Excel is more than sufficient if you only need to compute or visualise quick responses for small amounts of data. You will frequently have to perform the majority, if not all of these operations, in which case SQL and Excel must be used in tandem. SQL is the route to go if you have large databases, need to aggregate datasets fast, and want additional data protection. Additionally, SQL enables users to monitor data updates and set limitations to prevent other users from manipulating the data.
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