It’s true: SQL pivot and unpivot syntax are essential to data manipulation for analysts. It’s also true that SQL pivot—and especially SQL unpivot—statements are clunky, convoluted, and time-consuming to create. It leaves data managers asking, “Is there a better way to do SQL pivot and SQL unpivot statements?” The good news is there is a better way to create the necessary statements without the traditional SQL methods. Read on to learn about the traditional methods, the importance of using SQL pivot and unpivot commands, and how to overcome the difficulties and use pivot and unpivot to manipulate data more efficiently.
Traditional Pivot and Unpivot SQL Statements
To understand both the necessity of SQL statements and the challenges of it, it’s important to examine the traditional methods of using pivot and SQL unpivot statements. SQL is a programming language that can be used to manipulate databases to make data usable for analysis. Analysts can use SQL as a powerful tool to examine and analyze data, but using SQL well does require advanced technical knowledge.
An SQL pivot query aggregates data and connects it to show relationships. The pivot command turns unique values from one column into multiple columns. Here is an example of the syntax of an SQL pivot command:
That syntax is primarily only valuable to coders and developers because they understand it. Without the technical background, the query isn’t possible to make. The syntax isn’t intuitive. The output of the command is a table that displays the new columns and rows that are extremely valuable in analyzing the data. The key is finding a way to make a SQL pivot command easier.
After a pivot SQL command, there’s the SQL unpivot commands. Pivot and unpivot sound like opposites, but the unpivot command isn’t the true reverse of the pivot command. The unpivot command rotates columns into rows. The command doesn’t reproduce the original table before a pivot command because that command resulted in merged rows. Unpivot and T-SQL unpivot commands only rotate the existing columns, turning the SQL pivot columns to rows. Here is an example of the syntax of an SQL unpivot command:
The syntax for these unpivot commands is even more time-consuming and clunky than the pivot command. It takes training and time to be able to create these statements and get the output table.
So if both SQL pivot and unpivot statements are time-consuming and difficult to create, why do analysts continue to use them?
Pivot and Unpivot SQL Syntax Make Business Intelligence Viable
The reason? It’s powerful.
Like an Excel pivot table, an SQL pivot command is among the most helpful SQL statements, allowing data managers to organize and summarize information in new and original ways. The table helps show relationships and connections, all crucial in data analysis. In a similar manner, an SQL unpivot command normalizes data into a table that can be more easily analyzed and stored. Both are potent tools that facilitate data preparation and examination and enable analysts to make better decisions.
Coding SQL queries is an involved, specialized process that is not intuitive, takes ample time, involves several steps, and is susceptible to error. To be able to successfully create a query, an analyst will need to know how to code in SQL and have the training for these specific commands. And even trained coders can still have errors in their queries, and it can be time-consuming to iron out all the tiny syntax errors that can block accurate results. Still, SQL isn’t going away anytime soon. The querying language ties into far too many institutionalized databases, and it is used in several different functional areas across many industries. It’s a powerful language with many capabilities.
The key is to find a way to balance the benefits of SQL with the challenges by finding a more efficient and easier way to use SQL. While some analysts may consider that tool to be something in the distant future, the good news is the tool to make SQL unpivot and pivot commands intuitive and efficient already exists.
Designer Cloud Makes Business Intelligence Accessible
Since SQL and the data systems that leverage it are not going away anytime soon, Designer Cloud has integrated data connectivity into its process. Data connectivity is an increasingly necessary feature of all data tools. That’s why Designer Cloud democratized the data analysis process. With Designer Cloud, all users are enabled to make data-driven decisions, while still incorporating ways to connect data across several languages and databases. Long-winded SQL unpivot calls can be a thing of the past using Designer Cloud’s intuitive interface. The Designer Cloud interface can help users find the crucial info they need without the complicated SQL queries. Here’s how Designer Cloud makes SQL pivot and unpivot statements viable for data analysts:
- Connect. Don’t Fret. Designer Cloud’s range of connectivity options include key data processing languages and frameworks, including newer cloud-based systems like Amazon and Microsoft Azure to common relational systems, such as Oracle, Teradata, and SQL Server to Hadoop-based systems like HDFS and Hive / Impala. You gain usability without losing functionality.
- Non-technical Users Empowered. Designer Cloud permits all end-users—not just developers—the ability to probe and manipulate data without involving any technical syntax like SQL. Think of Designer Cloud as your custom SQL pivot and unpivot command coder, leaving you to focus on pulling critical information quickly from your data.
- Visual. Easy-to-use, interactive visuals replace longer script-writing. To manipulate and normalize your table, drag and drop with a few simple clicks replaces laborious SQL pivot and unpivot programming.
- Predictive. Designer Cloud’s transform builder thinks for you with handy and intelligent prompts. Once you institute an analysis, future manipulation can become automated and performed by default once Designer Cloud is familiar with your data.
Designer Cloud provides all users—not just those who can execute an SQL pivot or unpivot statement—to connect with data across multiple languages and systems. No longer do businesses have to rely on only those with extensive training to analyze the tables and data. With Designer Cloud, firms can engage with data in new ways, and it’s user-friendly to empower all users. Even with these features that make Designer Cloud easy to use, analysts don’t have to sacrifice the benefits of traditional SQL statements. This tool helps users balance the benefits with the challenges in a visual and easy-to-use tool.
To Learn how Designer Cloud can help make your SQL pivot and unpivot statements viable schedule a demo.