There are many ways of fetching data from databases. Most commonly, we can retrieve data from relational databases using API, SQL, or installing a database GUI tool, such as MySQL workbench, and get data by writing queries. To execute these processes, the users would normally have to write queries and install programs to process these queries to execute these actions. What if there is a way of avoiding writing any types of queries and still be able to fetch data from databases? In this post, I will be introducing how to request data from databases without writing SQL queries to ease the user experiences.
Most common platforms used to fetch and analyze data
Users of all skill levels will resort to different platforms to fetch data to further analyze and produce data insights that are beneficial to them. However, most of the methods and platforms users use tend to involve some form of coding or manual input to perform certain tasks and carry out actions. As we have seen, these methods might not be intuitive for users with no coding or data analysis background.
Many users will use Excel spreadsheets to import and export data to perform data analysis and manipulation functions. Under many circumstances, Excel spreadsheets are not the most suitable method for historical data storage. If an organization wants to update the spreadsheet for better management and administration, they often take the risk of losing huge amounts of historical data. This type of data loss creates further problems in data analysis, cleansing, manipulation, and comparisons, which will make it difficult to identify any type of beneficial and accurate data insights or trends.
Have you ever experienced typing long and wordy functions within Excel spreadsheets to perform a simple function to analyze data? The manual way often produces many errors not only within the function but also skews the data or produces completely inaccurate results that will only waste the time and efforts of the users. In addition, sometimes it requires users to follow through multiple steps of data transformation and formulas to execute actions and perform data analysis.
Before we dive into the topic of data retrieval and data analysis from databases. I would like to first introduce SQL, it stands for Structured Query Language. SQL is the standard programming language used to communicate with a database and relational database management systems. SQL statements and queries are powerful in the sense that the standard SQL commands such as "Select", "Insert", "Update", "Delete", "Create", and "Drop" can be used to perform tasks ranging from updating data on a database, retrieving data from a database, and inserting new data points into a database. Many companies store large amounts of data in relational databases so that the data can be easily pulled and analyzed to spot data trends and insights. SQL databases are suitable for heavy duty or complex transactions due to its stable and secure nature.
Even though SQL is suitable for big data analysis, not all users have the extensive coding knowledge that could manually write queries to perform desired actions towards the data being worked on. Not only will it be time consuming for users to learn the SQL syntax but it also takes time and manual labor to physically type the queries out in the SQL workbench to execute a simple task.
Cloud Database Management Platforms
There are many Cloud Database Management platforms such as Acho, where the users can have the flexibility to import large datasets from various resources and databases. Not only can the users import data from databases, they can also choose to import data from spreadsheets or third-party apps like HubSpot, Google Analytics, Stripe etc. through the use of API integration. Cloud database management platforms provide users with data scalability, meaning that importing large amounts of data can be easily handled in such platforms. In addition, cloud database management reduces the risk of data loss due to device damage or any type of unexpected hardware failure. To further ensure data protection, most cloud database management platforms have secured data protection measures and practices in place.
How to get data from databases without writing queries?
Acho Studio is a data management platform that allows users to easily migrate and scale data with the cloud in an efficient and secured way. Acho studio provides built-in SQL action that requires no coding, where all actions are performed in sequence. This not only eliminates the need for users to manually write SQL queries to execute actions, it also provides users of all skill levels a satisfied and intuitive experience to work with data.
After logging into your Acho Studio, you will be able to connect to databases such as MySQL, PostgreSQL, and SQL Server You will then have a view of a table with the imported databases where actions can be applied to manipulate, update, and analyze data without writing any code. The transformed data can then be exported out of Acho Studio with just a few clicks.
What are some actions that Acho Studio offers?
Currently, Acho offers a full suite of data cleaning and transformation tools available in no-code format, allowing you to do a quick analysis or search and eliminating the need to write complex expressions or code.
View - View actions allow you to change the display settings of your table.
Combine Table - Merge tables based on key columns for further data analysis and manipulation.
Transformation - Transformation actions allow you to change the schema of your table and transform it into a format that is suitable for your analysis.
Data Cleaning - Sometimes, there are some impurities in your data, such as incorrect data types, syntax errors, or missing values. These problems can cause some biases when you grasp insights from your data. Before doing any analysis, you can use Data Cleaning actions to deal with those impurities and make sure your data has a good quality.
Tools - Acho provides advanced tools to give you more flexibility to customize your data.
With the features from Acho, it allows the users with all backgrounds and skill levels to easily manipulate and analyze data. By eliminating the need to manually write SQL queries to fetch data, it not only saves time and effort but it also makes the data analysis process more intuitive.