• Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to footer
  • Articles
  • News
  • Events
  • Advertize
  • Jobs
  • Courses
  • Contact
  • (0)
  • LoginRegister
    • Facebook
    • LinkedIn
    • RSS
      Articles
      News
      Events
      Job Posts
    • Twitter
Datafloq

Datafloq

Data and Technology Insights

  • Categories
    • Big Data
    • Blockchain
    • Cloud
    • Internet Of Things
    • Metaverse
    • Robotics
    • Cybersecurity
    • Startups
    • Strategy
    • Technical
  • Big Data
  • Blockchain
  • Cloud
  • Metaverse
  • Internet Of Things
  • Robotics
  • Cybersecurity
  • Startups
  • Strategy
  • Technical

The Big Data Roadmap to a Winning Big Data Strategy

Dr Mark van Rijmenam / 5 min read.
May 15, 2013
Datafloq AI Score
×

Datafloq AI Score: 58.67

Datafloq enables anyone to contribute articles, but we value high-quality content. This means that we do not accept SEO link building content, spammy articles, clickbait, articles written by bots and especially not misinformation. Therefore, we have developed an AI, built using multiple built open-source and proprietary tools to instantly define whether an article is written by a human or a bot and determine the level of bias, objectivity, whether it is fact-based or not, sentiment and overall quality.

Articles published on Datafloq need to have a minimum AI score of 60% and we provide this graph to give more detailed information on how we rate this article. Please note that this is a work in progress and if you have any suggestions, feel free to contact us.

floq.to/8pU7H

Knowing what big data is, is one; knowing what a big data strategy is two; knowing how to implement that big data strategy is even more difficult. At least, that is how a lot of organisations perceive it. And it must be said, in large process-directed organisations, what most of the large corporates are, it can be difficult. Convincing the board and defining were to start could be a daunting task. While in fact the steps that need to be taken are clear and straightforward. This roadmap can help you in defining and implementing the right big data strategy.

Big Data RoadmapSo, there are four basics steps that you should follow to build a winning Big Data Strategy:

Understanding of Big Data at Board level and Management Support

Big Data means something different for any industry, any organization and every person. Therefore, it is important that organisations need to have a shared understanding what big data is to begin with. Otherwise defining a strategy is impossible. If this shared understanding is not present within your organization, everyone will start from their own point of view, resulting in a confused strategy.

Knowing what big data is can help you to get management buy-in at your organisation. Big data is a strategy matter, and not an IT matter. IT is merely supportive and therefore senior management or the board should be involved and support the decision to move forward with big data. Especially because in the beginning the returns on the investments made are still unclear and could potentially be negative in the beginning. Management support ensures that the project is not stopped before any real results can be shown.

Define Proof of Concepts and Stakeholders

When senior management or the board approves the decision to move forward, it is important to get together a multi-disciplinary team from all different departments within the organisation. Data tends to be kept in silos throughout the organisation, if you focus on only one part of the company, valuable data sources could be kept left out.

So, involve members from the marketing department to get the customer point of view. Involve product management to understand how data is gathered in the products or services offered. Involve human resources to understand the impact of data gathering on employees. Involve risk and compliance to ensure that your organisation sticks to the four ethical guidelines discussed earlier. Ensure the finance department to keep the budget under control and of course involve the IT department to build the necessary hardware and software.

Involving all departments within the organisation has a major advantage. When you start to define possible Proof of Concepts, the brainstorm sessions will become a lot better when people from different disciplines are involved. Each member of the multi-disciplinary big data team can offer a different point of view on data and together a large pool of possible use cases can be defined.

It is important during this phase to accept all possible use cases that are brought up during the brainstorm sessions (as in normal brainstorm sessions, no and thats not possible do not exist). It is essential to let creativity flow, as this will allow you to find new data sources previously not thought of.

Once you have outlined a few dozen possible use cases it is time to define criteria to rank all use cases. It will help to divide the use cases into different categories first, like use cases that fix bottlenecks or use cases that improve the efficiency of business processes. Use the criteria to rank all use cases in the different categories.


Interested in what the future will bring? Download our 2023 Technology Trends eBook for free.

Consent

Criteria can be the impact it has on IT, the impact to implement the suggested solution and/or a possible value proposition. It is no use to completely develop a scenario analysis for each use case, as there are too many unknowns at this moment.

Based on the criteria and the categories it is then time to select the Proof of Concepts that will be implemented. Define which stakeholders are important to involve in the project, next to the internal multi-disciplinary team. The multi-disciplinary big data team should be able to implement these Proof of Concepts with minimal efforts. It is better to fail fast and fail often than to develop a complete solution and in the end notice that a wrong turn was taken.

Although big data has the potential to bring a lot of positive results, it is likely that this is not visible from the beginning. Dont be afraid to fail and start over again in this phase, as it is part of the learning curve how to deal with big data and to better understand how your organisation can best benefit from it. For each organisation after all, the benefits will differ.

The moment the first results come in, it is time to share the results immediately with the entire organisation. Try to get the entire organisation involved in the big data efforts that are done, as this is a requirement for organisations to truly succeed with big data.

Define Processes, Turn Them Into Binary Code and Mix Datasets

Once you have started with a Proof of Concept, it is important to use a wide variety of data sources. More data sources will give you better insights, a process I like to call Mixed Data. When the required data sources are not available, look for possibilities to create them. You can think of adding sensors to your products to gather data or to purchase or download public and open data sets.

The next step is to develop the technology to analyse the data. You can use a multitude of analytics techniques such as data mining, clustering analytics or predictive analytics. The technology can exist of a Software-as-a-Service solution or a tailor-made solution, depending on the requirements.

Share Results, Change Culture and Improve

If the results of the Proof of Concepts are positive, it is time to expand the multi-disciplinary big data team throughout the organisation and to start more and larger projects. As the organisation has learned from the Proof of Concepts, it will be possible now to extrapolate the results of the first projects to the new projects. With the lessons learned it is feasible to better define a possible ROI, IT impact, possible process implications and other important criteria.

From there on, the entire process starts all over. For each new project that is done, it is of course important to fail less and implement faster, getting faster results and a more positive result. Whichever use case is chosen, in the end it will affect the net results of the organisation positively, as long as the big data projects are implemented wisely and correctly. Of course, this is not always easy so in case your organisation needs help, it is possible to contact us.

In the end, this roadmap can help your organisation develop and implement a big data strategy that is good for the company, good for your customers and good for society. Big data is too important and has too many implications and advantages to be ignored. So do not waste time and get started developing your big data strategy.

Categories: Big Data, Strategy
Tags: advice, Big Data, big data roadmap, criteria, Data, management buy-in, multi-disciplinary team, organisations, proof of concepts, results, roadmap, strategy, use cases

About Dr Mark van Rijmenam

Dr Mark van Rijmenam, CSP, is a leading strategic futurist and innovation keynote speaker who thinks about how technology changes organisations, society and the metaverse. He is known as The Digital Speaker, and he is a 5x author and entrepreneur.

Primary Sidebar

E-mail Newsletter

Sign up to receive email updates daily and to hear what's going on with us!

Publish
AN Article
Submit
a press release
List
AN Event
Create
A Job Post
Host your website with Managed WordPress for $1.00/mo with GoDaddy!

Related Articles

The Advantages of IT Staff Augmentation Over Traditional Hiring

May 4, 2023 By Mukesh Ram

The State of Digital Asset Management in 2023

May 3, 2023 By pimcoremkt

Test Data Management – Implementation Challenges and Tools Available

May 1, 2023 By yash.mehta262

Related Jobs

  • Software Engineer | South Yorkshire, GB - February 07, 2023
  • Software Engineer with C# .net Investment House | London, GB - February 07, 2023
  • Senior Java Developer | London, GB - February 07, 2023
  • Software Engineer – Growing Digital Media Company | London, GB - February 07, 2023
  • LBG Returners – Senior Data Analyst | Chester Moor, GB - February 07, 2023
More Jobs

Tags

AI Amazon analysis analytics app application Artificial Intelligence BI Big Data business China Cloud Companies company costs crypto customers Data design development digital environment experience future Google+ government information learning machine learning market mobile Musk news Other public research sales security share social social media software strategy technology twitter

Related Events

  • 6th Middle East Banking AI & Analytics Summit 2023 | Riyadh, Saudi Arabia - May 10, 2023
  • Data Science Salon NYC: AI & Machine Learning in Finance & Technology | The Theater Center - December 7, 2022
  • Big Data LDN 2023 | Olympia London - September 20, 2023
More events

Related Online Courses

  • Oracle Cloud Data Management Foundations Workshop
  • Data Science at Scale
  • Statistics with Python
More courses

Footer


Datafloq is the one-stop source for big data, blockchain and artificial intelligence. We offer information, insights and opportunities to drive innovation with emerging technologies.

  • Facebook
  • LinkedIn
  • RSS
  • Twitter

Recent

  • 5 Reasons Why Modern Data Integration Gives You a Competitive Advantage
  • 5 Most Common Database Structures for Small Businesses
  • 6 Ways to Reduce IT Costs Through Observability
  • How is Big Data Analytics Used in Business? These 5 Use Cases Share Valuable Insights
  • How Realistic Are Self-Driving Cars?

Search

Tags

AI Amazon analysis analytics app application Artificial Intelligence BI Big Data business China Cloud Companies company costs crypto customers Data design development digital environment experience future Google+ government information learning machine learning market mobile Musk news Other public research sales security share social social media software strategy technology twitter

Copyright © 2023 Datafloq
HTML Sitemap| Privacy| Terms| Cookies

  • Facebook
  • Twitter
  • LinkedIn
  • WhatsApp

In order to optimize the website and to continuously improve Datafloq, we use cookies. For more information click here.

Dear visitor,
Thank you for visiting Datafloq. If you find our content interesting, please subscribe to our weekly newsletter:

Did you know that you can publish job posts for free on Datafloq? You can start immediately and find the best candidates for free! Click here to get started.

Not Now Subscribe

Thanks for visiting Datafloq
If you enjoyed our content on emerging technologies, why not subscribe to our weekly newsletter to receive the latest news straight into your mailbox?

Subscribe

No thanks

Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

Necessary Cookies

Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.

If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.

Marketing cookies

This website uses Google Analytics to collect anonymous information such as the number of visitors to the site, and the most popular pages.

Keeping this cookie enabled helps us to improve our website.

Please enable Strictly Necessary Cookies first so that we can save your preferences!