Tag: data

Categories
Data Architecture Business Business Strategy Data Information Technology Legal Technology Strategy

The European Data Act: actually, can your data become a reliable source of income?

data economy 1

The European Data Act has recently been published.

It aims at clarifying and strengthening the governing framework of the #dataeconomy.

In the nutshell (extract):

“The Data Act will give both individuals and businesses more control over their data through a reinforced data portability right, copying or transferring data easily from across different services, where the data are generated through smart objects, machines, and devices.”

For example, a car or machinery owner could choose to share data generated by their use with its insurance company.

Such data, aggregated from multiple users, could also help to develop or improve other digital services, e.g. regarding traffic, or areas at high risk of accidents.”

Some thoughts on this

1️⃣ I wonder to what extent the boundaries of your data ownership can be explicitly defined, then transparently coded in IT systems, so that a “data asset” is legally bound to you as your property.

2️⃣ After this, you could ask Facebook, Instagram, and TikTok to share a piece of the cake: % of the revenue generated from your data.
Let’s face it, it looks like a game-changer, if it can really be implemented.

3️⃣ Ultimately, you can capitalize on GPDR architecture. It pushes the concepts of data ownership, consent management, data counters, data KPI, data censorship management, IAM, data expiry management, etc.

4️⃣ Beyond multicloud oversight solutions, this is an excellent use case for permissioned blockchain, like Hyperledger Fabric. (e.g. Infrachain )

5️⃣ Innovative business models to arise like “Mutual Data Funds”, or Open Data Lakes”, where a set of businesses or individuals would provide a set of qualified and certified data sources to act as “Value Added Data Sources”, something similar to Bloomberg or Reuters for financial News.

Also, these Mutual Data Pools are fitted to be plugged as Oracles in blockchains (#ethereum, #chainlink, #binance, etc.)

I can already envision the pitch of startups like “We are the Bloomberg of space mining Data” (which would be awesome by the way👍)

6️⃣ This could boost the API economy. But also push further the adoption of GraphQL and AsyncAPI standards.

7️⃣ I reckon open industry data models are a much better way to start. It would help regulators (e.g. Commission de Surveillance du Secteur Financier (CSSF) , CNPD – Commission nationale pour la protection des données , CNIL – Commission Nationale de l’Informatique et des Libertés), auditors and regtech (e.g. Scorechain ) to have a common ground to build their control frameworks and oversight infrastructure.
Now, it is time to stitch them together.

Links

Categories
Data Architecture Data Architecture Information Technology Master Data Management

Getting Started with Master Data Management (MDM)

data 1920
Image by Gerd Altmann

The MDM journey should definitely start with an analysis and the identification of the short-term goals you want to achieve. In fact, MDM will be a service for the whole company.

MDM is for:

  • A mall for your most valuable data
  • Contains end-to-end footprints of your business activities
  • An aggregation of rigorously organized data
  • Its scope starts with your core business information
  • Offers data-driven views of your processes that span over multiple lines of business.

You should start your MDM journey by:

  1. Analyze in detail the pros and cons of putting in place MDM. MDM is more about governance as distributed discipline than technology.
  2. Create a core project team that will analyze and defend the establishment of MDM in your company.
  3. Launch an awareness campaign. Then, educate people about the advantages and responsibilities when the business is operated with MDM
  4. Identify which data will be part of the MDM Strategy
  5. Define an Enterprise Data Model (EDM). This is a common catalog so that everybody in the company understands the business terms. Thus, it is also a means for calibrating internal communication. Ultimately, your MDM system is the digital implementation of your EDM
  6. Identify and standardize your Reference Data
  7. Design your Information System Architecture as to which data flows and systems will take part in it.
  8. Choose an MDM system technology. This application will be the core of the MDM execution and operations. Take into account the available skills on the market.
  9. Define your Data Quality Indicators because data quality management is paramount.
  10. Establish the MDM governance processes and roles (data owners and stewardship)
  11. Design your firsts reports and dashboards, then collect feedback about their value. As a result of this, increase the data scope by iteration.
  12. Communicate a LOT the benefits of MDM, to finally advertise the benefits. For instance, those would come from the golden data source, improved data quality, richer dashboards, unlocked analytics insights, etc.

Also, MDM is not a one-time exercise, it is a continuous practice. So make sure there is an organization owning the MDM system and the MDM governance!