Monday, March 1, 2021
  • Setup menu at Appearance » Menus and assign menu to Top Bar Navigation
Advertisement
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
No Result
View All Result
Home Neural Networks

How Do I Extract Panel Data From PDFs? First, Answer These 5 Questions

April 21, 2020
in Neural Networks
How Do I Extract Panel Data From PDFs? First, Answer These 5 Questions
585
SHARES
3.3k
VIEWS
Share on FacebookShare on Twitter
Extract Data From Complex Documents

Extracting panel data from PDF documents is not for the faint of heart. If you already read The Odd and Interesting Story of Panel Data, you’d know exactly what that means!

Typically it’s a time-consuming, manual (and some would say torturous) process that’s as tedious as it is filled with error.

You might also like

How AI Can Be Used in Agriculture Sector for Higher Productivity? | by ANOLYTICS

Future Tech: Artificial Intelligence and the Singularity | by Jason Sherman | Feb, 2021

Tackling ethics in AI algorithms: the case of Salesforce | by Iflexion | Feb, 2021

It’s all because of the challenges of extracting panel data.

It’s no secret that to extract panel data from PDFs is a pain. Those that do it know why:

  1. No universal format
  2. Different document types
  3. Variations in table formatting
  4. Scanned, handwritten specs
  5. Drawings spanning tens (or hundreds) of pages
  6. There’s never just one panel drawing
  7. And this list could go on and on….

So if it’s so tough, why isn’t there a fix?

Well…there is. The first step? Answer these five questions. Your answers will help you identify if your processes are broken, and if they are a good candidate for automation!

Shall we begin? (That’s not the first question! 😃)

QUESTION 1: Is Complete Panel Data Truly Necessary for Your Business?

If it sounds like an easy question, that’s because it is.

But, before you start down the path to automated data extraction from panel tables, it’s an important one to answer.

If you don’t truly NEED more accurate, complete data extracted from panel tables, then there’s no reason to invest the time and money to automate the process!

Jobs in Big Data

QUESTION 2: Imagine You Can Fully Automate Data Extraction from Panel Tables…What Would That Mean for Your Business?

Several years ago, a well-known global logistics company (UPS) ran a branding campaign that asked a question…”What can Brown do for you?”

Well, consider the automated data extraction version of that question!

What can automation do for you?

Don’t brush off answering this question. By thinking deeply about the effects of automation, you’ll come up with ways that automating the manual data extraction process can affect your business outcomes.

Here are some thoughts to get you started.

  1. Automation will reduce the time spent extracting data from panel tables. How will your employees use that time they get back?
  2. By using automation, the data you extract from the panel tables will be more accurate due to a lack of human error. What will more accurate data mean for other processes? For your organization?
  3. Automated data extraction means you’ll get more complete data, faster. How would more complete data extracted from panel tables impact your business?

QUESTION 3: Now That You’ve Uncovered the Possibilities, What Are the Processes and Functional Areas That Could Benefit from the More Complete, Accurate Data Extracted from Panels?

Find others in your organization that use — or could use — data from these documents. How might their workflows change if they were provided ready-to-be-consumed data?

In other words, it’s time to consider where you’d be able to use this data. How could it impact specific processes or functional areas?

Make a list! Make note of the process or functional area, then how more complete and accurate data pulled from the panel charts would help.

  1. [FILL IN PROCESS HERE]: [FILL IN WHAT BETTER DATA WOULD MEAN TO IT HERE]
  2. [FILL IN PROCESS HERE]: [FILL IN WHAT BETTER DATA WOULD MEAN TO IT HERE]
  3. [FILL IN PROCESS HERE]: [FILL IN WHAT BETTER DATA WOULD MEAN TO IT HERE]
  4. [FILL IN PROCESS HERE]: [FILL IN WHAT BETTER DATA WOULD MEAN TO IT HERE]
  5. [FILL IN PROCESS HERE]: [FILL IN WHAT BETTER DATA WOULD MEAN TO IT HERE]
  6. [FILL IN PROCESS HERE]: [FILL IN WHAT BETTER DATA WOULD MEAN TO IT HERE]
  7. (You get the drift, eh?)

QUESTION 4: Have You Attempted to Automate Data Extraction from Panel Tables in the Past, But Run Into Frustrating Barriers?

If panel data is critical to your business, then your answer to this question is almost certainly a YES!

In other words, if you have the need to automate, it’s likely you tried several ways to solve the problem, but ultimately ended up shelving your efforts.

Automation of data extraction from complex documents, like panel drawings, has been a challenge for a long time.

You’re not the first to hit roadblocks and postpone automation efforts. And, you won’t be the last.

The most important thing to take away from your answer to this question is this: As technology has evolved, so has the automation of data extraction.

Keep plugging. Don’t give up!

QUESTION: 5: As a Result of the Barriers (and your frustration), Have You Resigned Yourself to Using Manual Data Extraction for Panel Drawings?

That wouldn’t be surprising.

But, as alluded to in the last question, there’s another way!

Consider one particular Fortune 50 leader in engineering and manufacturing.

For more than a century, this stalwart has done business globally across multiple sectors, including aviation, power generation, healthcare, renewable energy, transportation, and finance.

To win business, the industry giant needs to respond to RFPs in a timely manner. Their biggest challenge in doing so? The RFP documents they receive are always free-flowing, often, spanning hundreds of pages with no fixed structure.

Like what you’ve probably experienced, their team would spend weeks extracting relevant information to be used in their quotations. The combination of the time it took to pull data and the risk of inaccuracies often cost the company their competitive advantage…and even affected how their brand was perceived.

Then, the company met Infrrd.

With the help of the Infrrd IDP Platform, an industry leader increased their data extraction accuracy by 90% (not a typo!) and they reduced the time to process the data from a single 200-page document from weeks to a few minutes.

What if you could reduce data extraction from panel tables from weeks to minutes?

If this Fortune 50 company can do it, so can you.

Explore the possibilities.

Automating panel data IS possible. And the effects it can have on your business may astound you.

Don’t give in to the limiting beliefs just because you already tried OCR or cloud automation tools from Amazon or Google.

If you’d like to explore the possibilities with someone who’s been there…or even just want some assistance figuring it all out, let’s chat.

Read more about how others have addressed their data extraction challenges head on and thrived.

OR…if you don’t want to wait to grow your business, chat with an expert right now!

Chat with an Expert

Finally, if you dig helpful content just like this…register to get it regularly!

Sign up for regular updates right to your inbox. 😁

Credit: BecomingHuman By: Infrrd

Previous Post

Customer Experience During a National Crisis: Real Customer-Centricity

Next Post

Google launches Cloud Healthcare API in general availability

Related Posts

How AI Can Be Used in Agriculture Sector for Higher Productivity? | by ANOLYTICS
Neural Networks

How AI Can Be Used in Agriculture Sector for Higher Productivity? | by ANOLYTICS

February 27, 2021
Future Tech: Artificial Intelligence and the Singularity | by Jason Sherman | Feb, 2021
Neural Networks

Future Tech: Artificial Intelligence and the Singularity | by Jason Sherman | Feb, 2021

February 27, 2021
Tackling ethics in AI algorithms: the case of Salesforce | by Iflexion | Feb, 2021
Neural Networks

Tackling ethics in AI algorithms: the case of Salesforce | by Iflexion | Feb, 2021

February 27, 2021
Creative Destruction and Godlike Technology in the 21st Century | by Madhav Kunal
Neural Networks

Creative Destruction and Godlike Technology in the 21st Century | by Madhav Kunal

February 26, 2021
How 3D Cuboid Annotation Service is better than free Tool? | by ANOLYTICS
Neural Networks

How 3D Cuboid Annotation Service is better than free Tool? | by ANOLYTICS

February 26, 2021
Next Post
Google launches Cloud Healthcare API in general availability

Google launches Cloud Healthcare API in general availability

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Recommended

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

January 6, 2019
Microsoft, Google Use Artificial Intelligence to Fight Hackers

Microsoft, Google Use Artificial Intelligence to Fight Hackers

January 6, 2019

Categories

  • Artificial Intelligence
  • Big Data
  • Blockchain
  • Crypto News
  • Data Science
  • Digital Marketing
  • Internet Privacy
  • Internet Security
  • Learn to Code
  • Machine Learning
  • Marketing Technology
  • Neural Networks
  • Technology Companies

Don't miss it

The Bayesian vs frequentist approaches: implications for machine learning – Part two
Data Science

The Bayesian vs frequentist approaches: implications for machine learning – Part two

March 1, 2021
Google’s deep learning finds a critical path in AI chips
Machine Learning

Google’s deep learning finds a critical path in AI chips

March 1, 2021
9 Tips to Effectively Manage and Analyze Big Data in eLearning
Data Science

9 Tips to Effectively Manage and Analyze Big Data in eLearning

March 1, 2021
Machine Learning & Big Data Analytics Education Market 2021 Global Industry Size, Reviews, Segments, Revenue, and Forecast to 2027 – NeighborWebSJ
Machine Learning

Machine Learning & Big Data Analytics Education Market 2021 Global Industry Size, Reviews, Segments, Revenue, and Forecast to 2027 – NeighborWebSJ

March 1, 2021
The Future of AI in Insurance
Data Science

The Future of AI in Insurance

March 1, 2021
Machine Learning as a Service (MLaaS) Market Analysis Technological Innovation by Leading Industry Experts and Forecast to 2028 – The Daily Chronicle
Machine Learning

Machine Learning as a Service (MLaaS) Market Global Sales, Revenue, Price and Gross Margin Forecast To 2028 – The Bisouv Network

March 1, 2021
NikolaNews

NikolaNews.com is an online News Portal which aims to share news about blockchain, AI, Big Data, and Data Privacy and more!

What’s New Here?

  • The Bayesian vs frequentist approaches: implications for machine learning – Part two March 1, 2021
  • Google’s deep learning finds a critical path in AI chips March 1, 2021
  • 9 Tips to Effectively Manage and Analyze Big Data in eLearning March 1, 2021
  • Machine Learning & Big Data Analytics Education Market 2021 Global Industry Size, Reviews, Segments, Revenue, and Forecast to 2027 – NeighborWebSJ March 1, 2021

Subscribe to get more!

© 2019 NikolaNews.com - Global Tech Updates

No Result
View All Result
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News

© 2019 NikolaNews.com - Global Tech Updates