4 Questions to Ask Before Starting a Big Data Project…

Up to 85% of big data projects fail, often because executives don’t accurately assess the project risks at the outset. Before investing in your next big data initiative, ask these four questions to determine its chances of success.

#1: Is your data valuable and rare? Not all available data is useful, nor is it unique or exclusive.

#2: Can employees use the data to create solutions on their own? You need to decentralize decision-making in order to encourage people to autonomously initiate, create, and adapt solutions.

#3: Can your technology actually deliver the solution? You can have all the data and ideas in the world, but if your technology can only deliver a prototype or a non-scalable solution, your project will fail.

#4: Is your solution compliant with laws and ethics? Even if it’s legal, if users find your solution to be “creepy,” the project is doomed from the start.

Go ahead and use these as your litmus paper test for Big Data Projects…

6 Ways to Go from Good to Great

What we can learn from Good-to-great companies?

How does strategic management differ at good-to-great companies versus mediocre ones?

# Finding a simple “Hedgehog concept (Shaded part – Intersection of passion, skill, and economic value)“ provides a clear path to follow.

 

# Success comes from many tiny incremental pushes in the right direction.

New technology should be viewed only as an accelerator toward a goal, not as a goal itself.

How do the people and culture differ at good-to-great companies versus mediocre ones?

Team drives successful transformations from good to great. Right people in the right place are the foundation of greatness.

Success requires confronting the nasty facts, while never losing faith. Leaders must create an environment where the brutal facts are aired without hesitation.

A culture of rigorous self-discipline is needed to adhere to the simple Hedgehog concept.

Follow the above steps to build a great company.

How to extract emails from multiple documents…

Here is simple ways to extract emails from PDFs, Microsoft Docs or Text Files with examples in Linux or Windows Cygwin:

1. Extract Emails from Microsoft documents (*.doc,*.docx):

  • Install tool catdoc using apt-get or yum or download in windows.
  • Copy all the docs in a single folder from which you want to extract emails.
  • Run the below command inside the folder:

for i in *.doc; do catdoc "$i" | grep -i -o '[A-Z0-9._%+-]\+@[A-Z0-9.-]\+\.[A-Z]\{2,4\}'; done

2. Extract Emails from PDFs:

  • Install tool pdf2txt.py using apt-get or yum or download in windows.
  • Copy all the pdfs in a single folder from which you want to extract emails
  • Run the below command inside the folder, and emails will be printed in console:

for i in *.pdf; do pdf2txt.py "$i" | grep -i -o '[A-Z0-9._%+-]\+@[A-Z0-9.-]\+\.[A-Z]\{2,4\}'; done

3. Extract Emails from textfiles:

  • Use grep command in linux/cygwin
  • Copy all the textfiles in a single folder
  • Run the below command and emails will be printed in console:

grep -i -o '[A-Z0-9._%+-]\+@[A-Z0-9.-]\+\.[A-Z]\{2,4\}'

Please share your comments below for any further details…