Data Preparation Statistics

Steve Goldstein
Steve Goldstein
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Data Preparation Statistics 2023: Facts about Data Preparation outlines the context of what’s happening in the tech world.

LLCBuddy editorial team did hours of research, collected all important statistics on Data Preparation, and shared those on this page. Our editorial team proofread these to make the data as accurate as possible. We believe you don’t need to check any other resources on the web for the same. You should get everything here only 🙂

Are you planning to form an LLC? Maybe for educational purposes, business research, or personal curiosity, whatever the reason is – it’s always a good idea to gather more information about tech topics like this.

How much of an impact will Data Preparation Statistics have on your day-to-day? or the day-to-day of your LLC Business? How much does it matter directly or indirectly? You should get answers to all your questions here.

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Top Data Preparation Statistics 2023

☰ Use “CTRL+F” to quickly find statistics. There are total 15 Data Preparation Statistics on this page 🙂

Data Preparation “Latest” Statistics

  • You can create high-quality ML training datasets with Amazon SageMaker Ground Truth Plus while lowering data labeling expenses by up to 40% without needing to create labeling apps or oversee a labeling staff on your own.[1]
  • Data preparation took up to 80% of the time consumed on an ML project. Employing specialized data preparation tools is essential to advance this process.[1]
  • Data flows through organizations like never before, from smartphones to brilliant cities as structured and unstructured data, where unstructured data makes up 80% of data now.[1]
  • According to the majority of industry observers, data preparation for business analysis or machine learning takes up 70% to 80% of data by scientists and analysts.[2]
  • Data scientists spend around 80% of their time preparing and maintaining data for analysis, with the collection of data sets taking up the remaining 19% of their time.[3]
  • 55% of poll participants agreed with Forrester’s forecast that machine learning would have or continue to have a substantial impact on their organizations and their departments during the next year.[3]
  • Data scientists consume 60% of their time cleaning and setting up data.[3]
  • 76% of data scientists consider data preparation as the barely enjoyable part of their work.[3]
  • According to Big Data Borat, data science is 99% of preparation and 1% of misinterpretation.[3]
  • Data scientists wish for more assistance and guidance from their management or executive team at 27%.[3]
  • 35% of data scientists presented their job with the highest value possible.[3]
  • Only 14% of data scientists thought they were being kept back by their mechanisms.[3]
  • According to 76% of data scientists, data preparation is the most difficult aspect of their work, yet clean data is the only way to produce effective and accurate business choices.[4]
  • According to data scientists and analysts, preparing data takes up 80% of their time instead of completing the analysis.[4]
  • In analytics applications, the 80/20 rule is often used, according to which 80% of the labor is stated to be spent on data preparation and collection and just 20% on data analysis.[5]

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How Useful is Data Preparation

One of the key reasons why data preparation is so important is that raw data is often messy and unstructured. In today’s world, data is being generated at an unprecedented rate from a wide range of sources, including social media, sensors, and mobile devices. This raw data can be full of errors, duplicates, missing values, and inconsistencies, making it unreliable and difficult to work with. Data preparation helps to address these issues by carefully cleaning and sorting the data so that it is accurate, complete, and consistent.

Furthermore, data preparation is essential for ensuring that the final analysis provides valuable insights and meaningful results. By transforming raw data into a structured and standardized format, analysts can more easily identify patterns, trends, and connections within the data. This makes it easier to draw conclusions, make predictions, and inform decision-making processes.

In addition to improving the quality of the analysis, data preparation also plays a critical role in maximizing the efficiency of the overall data analysis process. Without proper data preparation, analysts may waste valuable time and resources trying to clean and restructure the data during the analysis phase. This not only slows down the process but can also lead to errors and inconsistencies in the final results. By investing time and effort in data preparation upfront, analysts can save time and resources in the long run by ensuring that the data is ready for analysis when needed.

Another key benefit of data preparation is that it enables organizations to unlock the full potential of their data. By investing in proper data preparation techniques, organizations can leverage the full power of their data assets to drive innovation, improve efficiency, and gain a competitive edge in the marketplace. Whether it is for marketing, finance, operations, or any other business function, data preparation is essential for making data-driven decisions that can lead to success and growth.

In conclusion, data preparation is not just a necessary step in the data analysis process but is also a critical component for ensuring the accuracy, effectiveness, and efficiency of data-driven decision-making. By investing in proper data preparation techniques, organizations can unlock the full potential of their data assets and gain a competitive edge in today’s data-driven world. It may not always be the most exciting part of the data journey, but data preparation is undeniably useful and essential for any organization looking to succeed in the digital age.


  1. amazon –
  2. actian –
  3. forbes –
  4. talend –
  5. techtarget –

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