By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data-driven white label SEO
    Does Data Mining Really Help with White Label SEO?
    7 Min Read
    marketing analytics for hardware vendors
    IT Hardware Startups Turn to Data Analytics for Market Research
    9 Min Read
    big data and digital signage
    The Power of Big Data and Analytics in Digital Signage
    5 Min Read
    data analytics investing
    Data Analytics Boosts ROI of Investment Trusts
    9 Min Read
    football data collection and analytics
    Unleashing Victory: How Data Collection Is Revolutionizing Football Performance Analysis!
    4 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: 10 Simple Rules for Creating a Good Data Management Plan
Share
Notification Show More
Aa
SmartData CollectiveSmartData Collective
Aa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Privacy > 10 Simple Rules for Creating a Good Data Management Plan
Data ManagementPrivacy

10 Simple Rules for Creating a Good Data Management Plan

GloriaKopp
Last updated: 2017/07/20 at 10:37 AM
GloriaKopp
5 Min Read
Data Management Plan
SHARE

Part of business planning is arranging how data will be used in the development of a project. This is why you need a good, stable data management plan. This plan helps everyone involved know exactly what’s needed from them, and what to do if needed. Here’s how you can write a good data management plan in ten simple steps.

Contents
1. Define everyone’s roles2. Avoid the passive voice3. Outline what data is being collected4. Remove extra words5. Plan how you’ll collect data6. Decide how you’ll protect data collected7. Break up the text with headers8. Plan how data will be stored9. Use bullet points10. Write a summary

1. Define everyone’s roles

There could well be a lot of people involved in your project. However, even if there’s only two or three, you need to clearly define what everyone’s roles are. That way, when something needs to be done the plan can be consulted, and the right person given the task. It will save a lot of time in the long run, as no one will be passing jobs around looking for someone willing to take them on.

2. Avoid the passive voice

The passive voice is ambiguous because it doesn’t define the subject. This leads to planning documents that are harder to read, because the reader isn’t sure of what’s being said. “For example, ‘A fee needs to be paid before the plan be signed off on’ doesn’t tell us much. Instead, this should read ‘The developer will pay the fee because the Department Of Parks And Recreation will sign off on the plan.’”, – says Bethanie Loo, a Data Planner from Oxessays.

3. Outline what data is being collected

You want to be clear in what you’re actually collecting, and why. Make a list of every type of data that needs to be in your data plan, and the justification for doing so. This gives everyone a go to answer if questions need to be answered later on.

More Read

IoT Security

IoT Security: What Kind of Data Is Compromised by Poorly Protected IoT Devices?

Unleashing Victory: How Data Collection Is Revolutionizing Football Performance Analysis!
Strategies for Ensuring Security in Hyperconverged Infrastructure
What to Know Before Recruiting an Analyst to Handle Company Data
How Residential Proxies Help Improve Data Gathering

4. Remove extra words

As you write, be aware of how many words you’re using. Often, planning documents are bulked out by extra words and phrases that don’t add anything meaningful to the text. If it won’t get your point across, it needs to be cut.

5. Plan how you’ll collect data

You’ll need a plan to show how exactly you’re looking to collect data. There could be several different methods, so make sure that they’re all included. At least one person will need to be assigned the task of looking over this data as it’s being collected.

6. Decide how you’ll protect data collected

Once you have data, you’ll need to keep it protected as per the laws in your area. This is an important step, so be sure that you don’t skip it. Amber Coburn, an Operation manager at Essayroo comments the issue: “You also need to outline how you’ll assure that no plagiarism takes place, and cite all sources used”.

7. Break up the text with headers

As you write your plan, break up the text with headers. This clearly highlights what each section of your plan is about, making it much easier to read. As well as this, it will be easier to go back and find the information you need if you need it later on.

8. Plan how data will be stored

It’s vital that you know how your data will be stored. It needs to be somewhere secure, accessed only by authorised personnel. As well as this, you need to have back up plans, in case of hard drive failure or other disasters. A good way of doing this is by having it in at least two different physical locations. That way, if one fails you still have a back up.

9. Use bullet points

Plans are often much easier to read if you use bullet points. These are especially helpful when you’re detailing the steps needed to carry out your plan. It’ll be much easier for you when you want to look back at the plan later, so they’re often the best option.

10. Write a summary

At the end of your plan, write out a summary of everything that the plan covers. This means you have a short abstract of what the plan covers, and what should be done as a result of this piece of writing. It’s very helpful if you need an overview later on.

These ten tips will help you write the best data plan possible. Follow them, and you should be able to cover everything that you need.

TAGGED: data collection, data management, data management plan
GloriaKopp July 20, 2017
Share This Article
Facebook Twitter Pinterest LinkedIn
Share
By GloriaKopp
Follow:
Gloria Kopp is a business and data management consultant. She works as a content manager at Do my essay service. Besides, she is a regular contributor to such websites as Huffingtonpost, Engadget, Academized, etc. Read her latest post about Goassignmenthelp.

Follow us on Facebook

Latest News

sobm for ai-driven cybersecurity
Software Bill of Materials is Crucial for AI-Driven Cybersecurity
Security
IT budgeting for data-driven companies
IT Budgeting Practices for Data-Driven Companies
IT
machine,translation
Translating Artificial Intelligence: Learning to Speak Global Languages
Artificial Intelligence
data science upskilling
Upskilling for Emerging Industries Affected by Data Science
Big Data

Stay Connected

1.2k Followers Like
33.7k Followers Follow
222 Followers Pin

You Might also Like

IoT Security
Internet of Things

IoT Security: What Kind of Data Is Compromised by Poorly Protected IoT Devices?

6 Min Read
football data collection and analytics
Big Data

Unleashing Victory: How Data Collection Is Revolutionizing Football Performance Analysis!

4 Min Read
data center encryption
Security

Strategies for Ensuring Security in Hyperconverged Infrastructure

8 Min Read
analyst,women,looking,at,kpi,data,on,computer,screen
Analytics

What to Know Before Recruiting an Analyst to Handle Company Data

6 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 chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

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?