You have a large dataset from different sources with missing values, inconsistencies, and outliers. Before performing analysis, you need to clean and preprocess the data.
How do SAP Analytics Cloud’s automated data preparation features help you clean and structure your data for analysis, and how can these features save time in the data preparation process?
Ans: Using SAC’s automated data preparation features, we can streamline the cleaning & structuring of data for analysis. Features that can save time include:
Features that can help:
– Data Profiling & Validation which helps in identifying the missing values, removing duplicate entries, and providing a summary of the datasets by highlighting the inconsistencies.
– Data wrangling inkling merging of the datasets & performing transformations, aligning schemas, and resolving data format conflicts.
– Using the smart assist feature to convert data types, a grouping of datasets, combine columns, & clean data effectively based on detected patterns.
– Enriching the datasets by combining the structured and unstructured data for a more holistic view.
– No manual intervention while adding the dimensions or calculated measures in the tool.
Various benefits of these features in SAC’s data preparation features:
– Reducing the manual efforts by automating repetitive tasks such as missing values, detecting duplicates, etc.
– Instant preview of data to address the issues in real-time without switching the mode or tool.
– Minimal efforts are required to perform the complex cleaning & transformations.
– No external tools are required for enabling end-to-end workflows within SAC.
These are a few of the offerings by SAC features, that not only will save your time but also will improve the quality of the dataset, enabling faster & reliable insights.
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