Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: #14: Here’s a thought…
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > #14: Here’s a thought…
Business IntelligenceData MiningData VisualizationData Warehousing

#14: Here’s a thought…

brianfarnan1
brianfarnan1
6 Min Read
SHARE

An occasional series in which a review of recent posts on SmartData Collective reveals the following nuggets:

Credit where credit is due
In every case, market sectors were created or developed by small companies. Look at supply chain planning, warehouse management, human resources/human capital management, enterprise asset management, customer relationship management, sourcing and procurement, applications-as-a-service, and the nascent energy and emissions management markets.

—Bruce Richardson: “Who Drives Software Innovation? The Best-of-Breed vs. Giants’ Debate”

Be honest, now
Ask yourself if you know which customers are driving profits and which are destroying them? If not, this might be the best place to start thinking about improving insight and process improvement.

—Michael Ensley: “Focus on Operational Performance Management”


Well, it’s better than stealing
I recommend that all science grads read Tom Davenport’s book “Competing on Analytics.” It illustrates, with compelling examples, how businesses can benefit from using science and analytics. Several examples in Tom’s book come from Gary Loveman, CEO of Harrah’s Entertainment, [who has] famously said many times that there are …

More Read

Something Jeff Jarvis and I Agree On
Is AI-Generated Content a Net Positive for Businesses?
Podcast: Stand-Up Data Quality (Second Edition)
Self-Service BI & Adapting Line of Business (LoB) Executives
Location Based Business Intelligence


An occasional series in which a review of recent posts on SmartData Collective reveals the following nuggets:

Credit where credit is due
In every case, market sectors were created or developed by small companies. Look at supply chain planning, warehouse management, human resources/human capital management, enterprise asset management, customer relationship management, sourcing and procurement, applications-as-a-service, and the nascent energy and emissions management markets.

—Bruce Richardson: “Who Drives Software Innovation? The Best-of-Breed vs. Giants’ Debate”

Be honest, now
Ask yourself
if you know which customers are driving profits and which are
destroying them? If not, this might be the best place to start thinking
about improving insight and process improvement.

—Michael Ensley: “Focus on Operational Performance Management”


Well, it’s better than stealing
I recommend that all science grads read Tom Davenport’s book “Competing on Analytics.” It illustrates, with compelling examples, how businesses can benefit from using science and analytics. Several examples in Tom’s book come from Gary Loveman, CEO of Harrah’s Entertainment, [who has] famously said many times that there are three ways to get fired at Harrah’s: steal, harass women, or not use a control group. Business leaders across all industries are increasingly wanting data, analytics and scientific decision-making. Science grads have great training that enables them to take on these roles and to demonstrate the success of these methods.

—Karl Rexer (quoted in interview with Ajay Ohri): “Interview: Karl Rexer – Rexer Analytics”

Let’s hear it for the relational database
The Relational Database hasn’t maintained its dominance out of dumb luck. Instead, the RDBMS has consistently outperformed while providing the most general use capability of all the variety of platforms that have been available. Many other approaches have been tried; often, these have provided better object model integration (OODBMS) or better data model representation. But when the rubber has hit the road they have failed on one or more of the key staples of a DBMS – performance, scalability, security, reliability, recoverability and ease of use.

—Tony Bain: “Graph Databases and the Future of Large-Scale Knowledge Management”

You’re not alone
The real point, though, is (1) to be aware of your online presence, (2) to be aware that, if you’re online, you are adding to your (or detracting from) your brand, and (3) don’t let your online presence grow on its own—build a strategy and execute it consciously.

—Michael Fauscette: “Transparency and your online life”

Beware the random number generator
A recent discussion on r-help highlighted a similar security issue: a professor was considering using a random-number generator to generate questions for a student exam, until he learned that the random number stream (and therefore the answers) could be reverse-engineered in a matter of hours. (Then again, a student capable of that reverse-engineering task should be able to pass the exam with ease.)

—David M. Smith: “Engineering randomness”

It’s what they expect
When it comes to reporting, there’s a difference between the BI team and the rest of IT. The fact is that BI teams are successful not because of the infrastructure technologies, but because of the technologies in front of the users: the actual BI tool. To the end user, data visualization and access are much more important than database management and storage infrastructure. So when a new operational system is introduced, users expect the same functionality, look and feel as their other reports.

—Evan Levy: “No Data Warehouse Required: BI Reporting Extends Its Reach”
TAGGED:data qualityrelational database
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

AI role in medical industry
The Role Of AI In Transforming Medical Manufacturing
Artificial Intelligence Exclusive
b2b sales
Unseen Barriers: Identifying Bottlenecks In B2B Sales
Business Rules Exclusive Infographic
data intelligence in healthcare
How Data Is Powering Real-Time Intelligence in Health Systems
Big Data Exclusive
intersection of data
The Intersection of Data and Empathy in Modern Support Careers
Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Words at Work: Defining “Business Analytics”

4 Min Read

Top 10 interesting companies in Data Management

2 Min Read

#16: Here’s a thought…

7 Min Read
data integrity
Big Data

3 Huge Reasons that Data Integrity is Absolutely Essential

7 Min Read

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

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?