#SQLITE ORDER BY UPDATE#
The two big parts that enable this one-stop shop are database connection, query and update (with RSQLite), and analytics and visualization (with Shiny). To answer these questions, we need an environment where we can interact with the database and build data products. In order to review the budget, costs and revenue of the past few months, the following questions start to pop up in the heads of the managers: How many orders have been placed in the last quarter? What are the order details? What is the revenue of the last month? What do our sales look like across the country? What will the estimated sales revenue be for the next 6 months? And many more questions like these. In our story, we have a technology company, PineApple Inc. At one of their board meetings, the business managers are making budgets for the 2H FY (the second half of the fiscal year). The managers then will be able to see what they need immediately with a few points and clicks in an interactive environment. That’s what a one-stop shop is, and what this post is about.Īs shown in the bottom part of Figure 1, as opposed to the top part where the managers may easily lose their minds, a “data analyst” comes to help with the one-stop shop and a framework that integrates various kinds of requests made by the managers. How a data analyst comes to help with the one-stop shop The system takes care of itself, and it never sleeps while the back-end databases keep updating themselves.įigure 1. It grabs data from the databases, then processes the extracted data to generate business analytics, and incorporates the outputs in a decorated dashboard and report in the end. Therefore, ideally, there is a system that automates the repetitive queries. These requests are usually allocated to data analysts some of them are repetitive, time-consuming work that really can be automated.
To generate business intelligence, decision makers make ad hoc requests from time to time when the need emerges.
That’s what we call “business intelligence”.
When used effectively, data offer insights into a company’s business and strategies, and ultimately improve the company’s operations. In the course of a business process, a company produces data, collects its own data, and makes use of them. For instance, what is working well? And what calls for attention? Decision makers need the answers delivered to them timely across the departments, and presented to them effectively, better in real time with visual representations of the results. On a daily basis, decision makers sit on these data with untold stories and insights to be discovered. By default the order is always ASC ( Ascending ).īoth class and mark columns are in descending order.In the business world, with each transaction, tons of operational data are generated. We can use ASC for ascending order and DESC for descending order against each columns. Here is the output or error message we will get.Įrror: no such column: class1 Using ASC and DESC Let us change the query to q="SELECT * FROM student ORDER BY class1,mark", Note that there is no column as class1. Q="SELECT * FROM student ORDER BY class,mark " So first the order will be using class column and then within the class column mark is used from lowest ( mark ) to highest ( mark ) to order the records. In our query we will use two columns class and mark. We can display error message if there is any error by using try except. Q="SELECT id,name,class,mark,sex FROM student ORDER BY class DESC"
#SQLITE ORDER BY CODE#
In above code we changed the query part only by adding DESC. We can reverse the order ( from Z to A ) by using DESC. Print(row,row,row,row,row)īased on alphabetical forward order (from A to Z ) we displayed records based on class column in above code. Q="SELECT id,name,class,mark,sex FROM student ORDER BY class" As class column is storing text data, we will display rows in alphabetical order of class column. Order by query will take one or more column as input.
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