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
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
    cybersecurity efforts
    How Behavioral Analytics and AI Are Redefining Cybersecurity for Boca Raton Businesses
    14 Min Read
    data driven risk management in heatlhcare
    How Data Analytics Is Changing Healthcare Risk Management
    17 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: 5 Steps to Setting your Big Data Goals
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 > 5 Steps to Setting your Big Data Goals
AnalyticsData MiningHadoopPredictive Analytics

5 Steps to Setting your Big Data Goals

Joshua Polsky
Joshua Polsky
5 Min Read
Image
SHARE

ImageWe all have goals, or at least should.

ImageWe all have goals, or at least should. I’m reminded of a t-shirt that says, “If you don’t have goals, you’ll never score.” Meaning, if you don’t realize and set goals, you won’t get the desired outcome.In the context of Big Data, over half of projects started are never completed, and can even have very bad results.  

Having done both Big Data as well as BI projects before, we’ve learned not only what to do, but what not to do. If we could help even one person out there with this advice, it would make us all warm and fuzzy.

1) Your initiative needs a sponsor. Likely a C level employee within the organization that knows what value needs to come from the project. This person will take ownership of the project, and will be held accountable for failures and setbacks. He or she will check progress and milestones as well as address potential and actual blockers. It’s important that there is only one person overseeing the project, so that there aren’t instructions coming from various sources, resulting in people being pulled in different directions. On a positive note, the team members involved will know that they have one person to turn to, and that person is there with only one thing in mind, a clear vision of the outcome. Please note that this doesn’t mean there shouldn’t be other managers assisting, but everyone involved should be on the same page.   

More Read

How To Develop A Top-Notch Data Warehousing System
Big Data: The Secret Snacking Ingredient
How Predictive Analytics Is Redefining Risk Management Across Industries
The FTC Still Wondering If Cookies Can Behave…
Google’s coding standards for R

2) Define your business questions. Business questions are crucial to discovering what business problems exist, so they can be understood and solved for the betterment of the company. What do you want to know? Maybe you want to know which of your campaigns worked the best based on user acquisition rate by geography and/or time of day. Perhaps you want to know how to reduce product shrinkage or optimize your warehouse layout.  If you’re an ecommerce, it would be good to know the revenue at a product level as well as average customer support calls/chat/tickets for a specific time frame.  

3) Start small. Don’t bite off more than you can chew. Focus on the most important questions first. This is not easy because you probably feel, and rightfully so, that all questions are important. They are, but which is most pertinent to the project is what needs to be targeted at this juncture. Questions will evolve and new ones will be added. Stay focused, and handle them at a later stage.

4) Invest in understanding the data. Where is it? Which data is coming from where? The best way to handle this is the process of data profiling. Also, expect schema changes and plan for your system to be able to handle those changes. If you can identify the problem areas at the beginning, it will be less difficult and take less time to handle them up front as opposed to once the system is built. Lastly with your data, expect data corruption and just bad data in general. Again, plan for this up front, it will save headaches in the long run.  

5) Get an expert or two. You’ll need a technical expert that knows the ins and outs of the platform and how it is to be built. If your technical expert isn’t well versed in the business side of the company, get someone that does.  He or she should know every aspect of the business model, the finances, the products and/or services, and how it is all tied together.  

This process will not be easy, but it will make going forward easier than if you did not undertake it at all. 

original post

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Industrial IoT (IIoT) Implementation: A Step-by-Step Guide for Manufacturers -- AI-generated illustration
Industrial IoT (IIoT) Implementation: A Step-by-Step Guide for Manufacturers
Exclusive
How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
Analytics Big Data Exclusive Predictive Analytics
Top 20 Git Commands for Modern Development -- AI-generated illustration
Top 20 Git Commands for Modern Development
Exclusive
managed device response
Why MDR Is Essential for Big Data Security
Big Data Exclusive Security

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

US computer scientists have found that random networks – the…

1 Min Read

Data Mining: Widespread Acceptance When?

1 Min Read

Predictions for 2009

6 Min Read

Honing in on the Value of Social Media Data

4 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
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?