Data preparation forms the bedrock upon which insightful analysis and informed decision-making stands, directly impacting business revenue. However, preparing data is often considered a complex and time-consuming task that requires IT intervention. A Forbes report found that 80% of total analysis time goes to data preparation alone, with just 20% left over for core analysis.
While this process might be challenging, modern BI platforms continue to innovate with AI and automation, to offer self-serviceable capabilities that make data preparation accessible to all users. In this blog, we explore effective strategies and key capabilities to make your data analysis-ready.
3-pillar strategy
We've condensed various data preparation best practices into this straightforward 3-pillar strategy.
These best practices will help you identify data roadblocks and effectively overcome them with advanced data preparation.
Data modeling
All business operations are interlinked and generate inter-related data. Data modeling involves identifying and organizing these relationships, such as how marketing efforts lead to sales and convert into revenue.
To understand the performance of individual business units or the business as a whole, it’s essential to model the interrelated data, in order to uncover the cross-functional impacts of different operations on each other. A well-designed data model ensures data integrity and reliability, providing a comprehensive view of business dynamics.
BI platforms now support the auto modeling and auto joining of relevant datasets—and for tasks requiring code, they offer natural language prompts to generate the code necessary for analysis. In the following demo video, we use a natural language prompt to perform a union of two datasets, showcasing a key generative AI capability of the platform.
Watch our complete webinar on data preparation to learn more about data modeling.
Data transformation
Data modeling adds meaning to data at the table or dataset level, while data transformation enhances the meaning of individual columns within a table. Oftentimes, data columns need to be reformatted to make them ready for specific analysis; this can involve setting conditions for the column, such as defining the data type and ensuring that values adhere to a specific format or pattern, like date formats or currency symbols. This standardizes the data within your system.
In the following demo video, we demonstrate how to create a new column to calculate the duration of a task by applying a formula to existing columns, using a prompt in natural language.
Data enrichment
Data enrichment aims to make data more meaningful at the unit level within a table. Even after standardizing your data at the column level, discrepancies can still exist in individual values. These issues can include incorrect data, missing values, duplications, and more. Data enrichment involves cleaning this data to ensure its quality. This process underpins the confidence businesses have in data-driven decisions, by ensuring every last value is correct in your data table.
Data enrichment often requires advanced AI capabilities. In the demo video below, we use an AI feature called "cluster and merge" to automatically detect and correct clusters of misspelled brand names in seconds. This significantly reduces the time needed to standardize values across a column.
Conclusion
By adopting a 3-pillar strategy—data modeling, data transformation, and data enrichment—businesses can effectively identify and overcome data roadblocks. This strategy ensures data integrity, enhances the depth of analysis, and maintains the highest quality of data.
With current AI advancements, we anticipate transformative capabilities in this space; ones that will simplify complex tasks and automate routine processes. Advanced language models, such as ChatGPT, will further enhance interactions, making them more human-like and democratizing data analytics. Additionally, noteworthy trends in data preparation include prioritizing data security and embracing real-time data management for more efficient workflows.
Watch our complete webinar as we go over even more data preparation capabilities.
You can also sign up for Zoho Analytics today—or enjoy a free personalized demo from one of our experts!
Comments