By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    football analytics
    The Role of Data Analytics in Football Performance
    9 Min Read
    data Analytics instagram stories
    Data Analytics Helps Marketers Make the Most of Instagram Stories
    15 Min Read
    analyst,women,looking,at,kpi,data,on,computer,screen
    What to Know Before Recruiting an Analyst to Handle Company Data
    6 Min Read
    AI analytics
    AI-Based Analytics Are Changing the Future of Credit Cards
    6 Min Read
    data overload showing data analytics
    How Does Next-Gen SIEM Prevent Data Overload For Security Analysts?
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: The Napoleonic Wars – Timely and Near Enough was Good Enough
Share
Notification Show More
Aa
SmartData CollectiveSmartData Collective
Aa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > The Napoleonic Wars – Timely and Near Enough was Good Enough
Uncategorized

The Napoleonic Wars – Timely and Near Enough was Good Enough

TeradataAusNZ
Last updated: 2009/09/21 at 1:03 PM
TeradataAusNZ
5 Min Read
SHARE

In 1815, they didn’t have access to all the information we have today, but sometimes they had the right information when they needed it. Take the Duke of Wellington, for instance. Knowing that Napoleon had 14,000 seasoned cavalry, what the French infantry tactics were, and capitalizing on the bad weather to contain the French, he had the right information at the right time to confidently act and win the Battle of Waterloo.

Arguably the most important gap in his intelligence for the day was whether his Prussian allies would arrive on time… Other helpful information could have been amassed about the very high-stakes decision he was about to make but this would have taken time. Wellington made his decision on aspects of the coming battle based on key indicators that were clear, not exact. Knowing the exact number of enemy cavalry or bayonets, sabres and muskets, the names of French Colonels and insignia of their units would have perhaps proved helpful. These were not critical when deciding to act on the threat of Napoleon’s army at Waterloo. He used the information he had to make the right decision at the right time to lead his troops to victory.

Today, data quality is something …

More Read

analyzing big data for its quality and value

Use this Strategic Approach to Maximize Your Data’s Value

7 Data Lineage Tool Tips For Preventing Human Error in Data Processing
Preserving Data Quality is Critical for Leveraging Analytics with Amazon PPC
Quality Control Tips for Data Collection with Drone Surveying
3 Huge Reasons that Data Integrity is Absolutely Essential

In 1815, they didn’t have access to all the information we have today, but sometimes they had the right information when they needed it. Take the Duke of Wellington, for instance. Knowing that Napoleon had 14,000 seasoned cavalry, what the French infantry tactics were, and capitalizing on the bad weather to contain the French, he had the right information at the right time to confidently act and win the Battle of Waterloo.

Arguably the most important gap in his intelligence for the day was whether his Prussian allies would arrive on time… Other helpful information could have been amassed about the very high-stakes decision he was about to make but this would have taken time. Wellington made his decision on aspects of the coming battle based on key indicators that were clear, not exact. Knowing the exact number of enemy cavalry or bayonets, sabres and muskets, the names of French Colonels and insignia of their units would have perhaps proved helpful. These were not critical when deciding to act on the threat of Napoleon’s army at Waterloo. He used the information he had to make the right decision at the right time to lead his troops to victory.

Today, data quality is something most organizations still grapple with, with varying degrees of success and consensus. Add to this the issue of having “all the detail,” rather than just the information that is needed for decision-making or core business process, and intelligence-based decision-making becomes a dream rather than a reality.

Data quality issues can result in mistakes being made when the wrong information is provided to the right person at the right time. Often this leads to a case of organizations being “once bitten, twice shy.” The practical realities of what data is relevant to whom, when they need it and what this is used for often do not gel with ideals of data quality perfection and having all enterprise data considered in decision making. There is no point having the cleanest, parsed and transformed data and “nice to know” information on a customer who is at risk of buying from another company once they have already left. Being confident in the quality of the information and being able to assess the relevant risks is what is most important when acting on intelligence.

The pursuit of Data Quality perfection and trying to get all the data available rather than what is needed now can slow (and sometimes cripple) an organization’s ability to respond to the near-to-real time demands of their operating environment. Knowing what is important and understanding the risks and opportunities and how quickly you need to act is the key. Predicting, knowing what will, or will most likely happen in your business before an event is the insight that gives some of Teradata’s most successful customers the competitive edge to act. The right information, on enough of the right indicators results in right-time action.

When is information too much and when is it not enough, and how do you know with confidence which you have?

David Bremstaller

http://www.linkedin.com/pub/david-bremstaller/a/360/a24

TAGGED: data quality
TeradataAusNZ September 21, 2009
Share This Article
Facebook Twitter Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Shutterstock Licensed Photo - 1051059293 | Rawpixel.com
QR Codes Leverage the Benefits of Big Data in Education
Big Data
football analytics
The Role of Data Analytics in Football Performance
Analytics Big Data Exclusive
smart home data
7 Mind-Blowing Ways Smart Homes Use Data to Save Your Money
Big Data
ai low code frameworks
AI Can Help Accelerate Development with Low-Code Frameworks
Artificial Intelligence

Stay Connected

1.2k Followers Like
33.7k Followers Follow
222 Followers Pin

You Might also Like

analyzing big data for its quality and value
Big Data

Use this Strategic Approach to Maximize Your Data’s Value

6 Min Read
data lineage tool
Big Data

7 Data Lineage Tool Tips For Preventing Human Error in Data Processing

6 Min Read
data quality and role of analytics
Data Quality

Preserving Data Quality is Critical for Leveraging Analytics with Amazon PPC

8 Min Read
data collection with drone use
Data Collection

Quality Control Tips for Data Collection with Drone Surveying

9 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Lost your password?