What is Data Preparation?
Data preparation is the process of cleaning, reformatting and modeling your data in order to get it into shape for analytics or other evaluation purposes. Properly cleaning and wrangling data will probably be the most time-consuming portion of the data scientist’s workload, but it is essential to error-free analysis and richer data insights.
Sisense In Warehouse Data Prep
In-Warehouse Data Prep gives builders advanced functionality to rapidly transform and optimize raw data using materialized views on cloud data warehouses. Learn why data analysts love it, and how it helps drive faster analytics for everyone.
Data preparation steps
There are many paths you can take to arrive at your end goal of properly prepped data, depending on your particular situation and set-up. Here is an overview of the phases of a typical data preparation process:
- Define: Nail down your business requirements and end goals, including all the questions that you want your data to answer.
- Identify: Collect the relevant data sources required to answer the business questions. A complete data catalog can make this step easier.
- Transform: Wrangle the raw data into a format more suited for analytical processing
- Model: Define the relationship between data entities
- Load: Convert the data into a data mart, data warehouse or analytical database
- Verify: Check the accuracy of your results against known metrics
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Why is Data Preparation Important?
The preparation of data dictates the types of analysis and reporting that can be performed from the front-end of the data analytics solution. Data preparation for analytics makes it easier for end users to get answers to their business questions in a straightforward fashion. Furthermore, effective data modeling and ETL processes could have a major impact on the overall performance of the BI solution.
Benefits of data prep
A thorough data preparation process can give your organization advantages Before you use your data for analysis or plug it into dashboards and visualizations, it must be clean and free of errors. Preparing data for analysis will help you avoid mistakes, which will save you time down the line.
These errors will be much more difficult to catch and fix after the data has been transferred out of its original format. Using properly cleaned and formatted data in your cloud applications will ensure top-quality reporting and analysis. And this will help you get to your game-changing business insights.
Tired of the data prep grind? Let Sisense lighten your load. Prep, manage, and secure your data easily and intuitively, no supplemental tech or IT help required.
Cloud data preparation
In addition to being good business practice, preparing data for analysis can be an integral part of the cloud migration process. Performing your organization’s data prep in the cloud means it won’t require staff resources for technical installations, and all your organization’s departments can access it, leading to better collaborations.
The adaptability that cloud storage offers means your data preparation can scale up as your business grows. It also means that someone else is looking out for bug fixes and cool new program features, so your data will always be ready to benefit from new innovations on the market
Simplifying Data Preparation for Faster Analytics
Sisense has developed unique In-Chip™ technology that enables its business intelligence software to process large and disparate datasets at unparalleled speeds. This translates into less need to create complex data models and eliminates much of the preprocessing required before jumping into visual analytics.
Check out this webinar on demystifying data modeling to learn more about how Sisense’s solution simplifies every step of the process when working with complex data.Start Free Trial Back to Glossary