A simple drag and drop of action to flexibly work with strings, arrays, objects, and more.
Bucketing/Binning
Grouping by a range of values, i.e., categorizing a number of continuous values into a smaller number of bins (buckets), say, from {1,3,5…} to {1-5, 8-10, 14-18…}.
Actions Object String are commonly used to perform the bucketing.
Data Aggregation
The process where data is gathered and expressed in a summary form for statistical analysis and visualization. For example, data can be aggregated over a given time to provide statistics such as average, minimum, maximum, sum, and count. The aggregated data then can be analyzed to gain insights about particular resources or resource groups.
Actions Iteration/Map Array String are commonly used to perform the aggregation.
Data Cleansing
The process of analyzing, identifying, and correcting messy, raw data. Also referred to as data scrubbing and data cleaning, data cleansing relies on the careful analysis of datasets to provide the most accurate data possible.
Actions Iteration/Filter Data/Set String are commonly used to perform the cleansing.
Data Deduplication
The process eliminates excessive copies of data and significantly decreases storage capacity requirements. Also referred to as single-instance storage, intelligent compression, commonality factoring, or data reduction, deduplication allows you to store one unique copy of data in your data warehouse or database.
Actions Array/Unique Conditional/IF are commonly used to perform the dupulication.
Data Derivation
The creation of special rules to “derive” the specific information you want from the data source. For example, let's say you have revenue data from sales, but you want the profit figures derived after subtracting costs and tax liabilities.
Actions Interation/ForEach Data/Expression are commonly used to perform the derivation.
Data Filtering
The process of refining the datasets. The goal is to eliminate repeated, irrelevant, or overly sensitive data.
Actions Interation/Filter are commonly used to perform the filtering.
Data Integration & Merge
The process of merging the data into the same structure or schema. Used for data warehousing purposes, data integration supports the processing of massive data sets by merging multiple data sources into an easy-to-analyze whole.
Actions Interation/ForEach String/Join Database are commonly used to perform the integration.
Data Joining
The process of connecting two or more database datasets. This allows a relationship between multiple datasets, which merges data together so you can access correlated data from multiple sources.
Actions Interation/Map String/Join are commonly used to perform the integration.
Data Splitting
The process of dividing a single column into multiple columns. For example, splitting the single column into multiple columns can be useful to develop "training" and "testing" sets. Data splitting is also used to split a large amount of data gathered over a period of time.
Actions Array/Split String/Split Object/Split are commonly used to perform the splitting.
Data Summarization
Similar to data aggregation, it refers to presenting the summary of generated data in an easily comprehensible and informative manner. For example, the sum of the total revenue of all the sales or by an individual salesperson, then for Head of Sale, you create sales metrics that reveal total sales in a time-periods.
Actions Iteration/Map Data/Expression String/Join are commonly used to perform the Summarization.
Data Validation
The process of creating rules for the system to handle different data issues. A Common use case is to ensure the accuracy and quality of the data you transform.
Actions Condition/Match Interation/Any-is-true are commonly used to perform the Validation.
Format Revision
The process of fixing problems that stem from fields having different data types. For example, some fields might be numeric, and others might be text.
Actions String/to-Integer Array/to-Object JSON/Decode DateTime/Unix-to-UTC are commonly used to perform the formatting.
Key Restructuring
The process of transforming to generic keys whether in a database or data object. For example, when the data has keys with built-in meanings, serious problems can develop when the key needs to be changed.
Actions Iteration/Find-Index Object/Keys Database are commonly used to perform the formating.
Z-Score Normalization and Max-Min Scaling
Though not a common use case for API AutoFlow, Z-Score and min-max normalization usage is becoming common for data scientists. By applying the formula once in the `data/Expression` action, the incoming data can be normalized in real-time.
Actions Data Expression is commonly used to perform the Z-Score normalization.