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
    unusual trading activity
    Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
    3 Min Read
    software developer using ai
    How Data Analytics Helps Developers Deliver Better Tech Services
    8 Min Read
    ai for stock trading
    Can Data Analytics Help Investors Outperform Warren Buffett
    9 Min Read
    media monitoring
    Signals In The Noise: Using Media Monitoring To Manage Negative Publicity
    5 Min Read
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: The ‘Time’ Factor in Data Management
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > Decision Management > The ‘Time’ Factor in Data Management
Decision Management

The ‘Time’ Factor in Data Management

SteveSarsfield
SteveSarsfield
7 Min Read
SHARE

I’ve been thinking about how many ways time influences the data management world.

I’ve been thinking about how many ways time influences the data management world. When it comes to managing data, we think about improving processes, coercing the needs and desires of people and how technology comes to help us manage it all. However, an often overlooked aspect of data management is time. Time impacts data management from many different directions.

Time Means Technology Will Improve
As time marches on, technology offers twists and turns to the data steward through innovation.  20 years ago, mainframes ruled the world.  We’ve migrated through relational databases on powerful servers to a place where we see our immediate future in cloud and big data. As technology shifts, you must consider the impact of data.

The good news is that with these huge challenges, you also get access to new tools.  In general, tools have become less arcane and more business-user focused as time marches on. 

Time Causes People to Change

Like changes in technology, people also mature, change careers, retire. With regard to data management, the corporation must think about the expertise needed to complete the data mission. Data management must pass the “hit by a bus” test where the company would not suffer if one or more key people were to be hit by a Greyhound traveling from Newark to Richmond.

More Read

Can good decisions have bad outcomes?
How to Use Pivot Tables to Mine Your Data
Dell Offers VoC Advice to Other Companies
First Look – Starview
Bridging the Communications Gap Between Utilities and Consumers

Here, time is requiring us to be more diligent in documenting our processes.  It is requiring us to avoid undocumented hand-coding and pick a reproducible data management platform.  It helps to have third-party continuity, like consultants who, although will also experience changes in personnel, will change on a different schedule than their clients.

Time Leads to Clarity in the Imperative of Data Management

With regard to data management, corporations have a maturity process they go through. They often start as chaotic immature organizations and realize the power of data management in a tactical maturity stage. Finally, they realize data management is a strategic initiative when they begin to govern the data.  Throughout it all, people, process and technologies change.

Knowing where you are in this maturity cycle can help you plan where you want to go from here and what tactics you need to put in place to get there. For example, very few companies go from chaotic, ad hoc data management to full-blown MDM. For the most part, they get there through making little changes, seeing the positive impact of the little changes and wanting more. Rather, a chaotic organization might be more apt to evolve their data management maturity by consolidating two or more ERP systems and revel in its efficiency.

Time Prevents Us from Achieving Successful Projects
When it comes to specific projects, taking too much time can lead to failure in projects.  In the not so distant past, circa 2007, the industry commonly took on massive, multi-year, multimillion dollar MDM projects. We now know that these projects are not the best way to manage data. Why? Think about how much your own company has changed in the last two years.  If it is a dynamic, growing company, it likely has different goals, different markets, different partners and new leadership. The world has changed significantly, too.  Today’s worldwide economy is so much different that even one year ago. (Have you heard about the recession and European debt crisis?) The goals of a project that you set up two years ago will never achieve success today.

Time makes us take an agile approach to data management. It requires that we pick off small portions of our problems, solve them, prove value and re-use what we’ve learned on the next agile project.  Limit and hold scope to achieve success.

Time Achieves Corporate Growth (which is counter to data management)
Companies who are just starting out generally have fewer data management problems than those who are mature. Time pushes our data complexity deeper and deeper. Therefore time dictates that even small companies should have some sort of data management strategy.  The good news is that now achievable with help from open source and lower cost data management solutions. Proper data management tools are affordable by both Fortune 1000 and small to medium-sized enterprises.

Time Holds Us Responsible
That said, the longer a corporation is in business, the longer it can be held responsible for lower revenue, decreased efficiency and lack of compliance due to poor data management. The company decides how it is going to govern (or not govern) data, what data is acceptable in the CRM and who is responsible for the mistakes that happen due to poor data management. The longer you are in business, the more responsible the corporation is for its governance. Time holds us responsible if the problems aren’t solved.

Time and Success Lead to Apathy

Finally, time often brings us success in data management.  With success, there is a propensity for corporations to take the eye off the prize and spend monies on more pressing issues.  Time and success can lead to a certain apathy, believing that the data management problem is solved.  But, as time marches on, new partners, new data sources, new business processes. Time requires us to be ever vigilant in our efforts to manage data.

Covering the world of data integration, data governance, and data quality from the perspective of an industry insider.
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

AI in branding
How Data Analytics and Data Mining Strengthen Brand Identity Services
Big Data Exclusive
Hidden AI, a risk?
Hidden AI, Real Risk: A Governance Roadmap For Mid-Market Organizations
Artificial Intelligence Exclusive Infographic
unusual trading activity
Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
Analytics Exclusive Infographic
Ai agents
AI Agent Trends Shaping Data-Driven Businesses
Artificial Intelligence Exclusive Infographic

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Tuesday Night Massacre Hurt Watson’s Ratings

2 Min Read
Data-Driven Design
Big DataDecision Management

Data-Driven Design: A Beautiful Opportunity or a Massive Headache?

5 Min Read
Excel
Data ManagementData WarehousingDecision ManagementSoftware

How Excel Can Help You Measure Value and Engagement

9 Min Read

Improvement Project for Services; Remember You’re Never Really Done

8 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 in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

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

Sign in to your account

Username or Email Address
Password

Lost your password?