Tag: Data

Untangling TOGAF’s C-MDM (Master Data): A Friendly Guide

Untangling TOGAF’s C-MDM (Master Data): A Friendly Guide

Hey Tech Friends,

Let’s decode the TOGAF® Series Guide: Information Architecture – Customer Master Data Management (C-MDM). This document isn’t just about mastering data; it’s a journey into the heart of harmonizing customer data across an organization. C is for the stage in the ADM cycle, and MDM is all about the enterprises’ data.

The Core Idea: C-MDM is all about streamlining and enhancing how an organization manages its customer data. It’s like giving every customer information a VIP treatment, ensuring it’s accurate, accessible, and secure.

Generic Description of the Capabilities of the Organization

Sources: https://pubs.opengroup.org/togaf-standard/master-data-management/index.html (inspired by Michael Porter’s value chain)

Why It Matters: In our tech-driven world, customer data is gold. But it’s not just about having data; it’s about making it work efficiently. C-MDM is the toolkit for ensuring this data is managed smartly, reducing duplication, and enhancing access to this vital resource.

The TOGAF Twist: The guide integrates C-MDM within TOGAF’s Architecture Development Method (ADM). This means it’s not just a standalone concept but a part of the larger enterprise architecture landscape. It’s like having a detailed map for your journey in data management, ensuring every step aligns with the broader organizational goals.

Key Components:

  1. Information Architecture Capability: Think of this as the foundation. It’s about understanding and handling the complexity of data across the organization.
  2. Data Management Capabilities: This is where things get practical. It involves managing the lifecycle of data – from its creation to its retirement.
  3. C-MDM Capability: The star of the show. This section delves into managing customer data as a valuable asset, focusing on quality, availability, and security.
  4. Process and Methodology: Here, the guide adapts TOGAF ADM for C-MDM, offering a structured yet flexible approach to manage customer data.
  5. Reference Models: These models provide a clear picture of what C-MDM entails, including the scope of customer data and detailed business functions.
  6. Integration Methodologies: It’s about fitting C-MDM into the existing IT landscape, ensuring smooth integration and operation.

What’s in It for Tech Gurus? As a tech enthusiast, this guide offers a deep dive into managing customer data with precision. It’s not just about handling data; it’s about transforming it into an asset that drives business value.

 C-MDM capability

Sources: https://pubs.opengroup.org/togaf-standard/master-data-management/index.html

So, whether you’re an enterprise architect, data manager, or just a tech aficionado, this guide is your compass in navigating the complex world of customer data management. It’s about making data not just big, but smart and efficient.

Happy Data Managing!

PS: Fostering a culture of data-driven decisions at all levels of your organisation, from value streams in the Business Domain to Observability in the Technology Domain, will allow your stakeholders and teams to make better strategic and tactical decisions. Invest wisely here and ensure insights are accessible to all key stakeholders – those stakeholders that have the influence and vested interest. This is where AI will revolutionise data-driven decisions; instead of looking at reports, you can “converse” with AI about your data in a customised reference vector DB.

References:

AI Chatbots to make Data-Driven Decisions

Sources: https://pubs.opengroup.org/togaf-standard/master-data-management/index.html

Getting started with Amazon SQS

The data and metadata inflection point

We are nearing an inflection point regarding technology and data. Data is basically gold. In the next 30 years you will basically have a life logger app and many connected/smart devices. You will be able to rewind back in time and listen/look at a conversation you had with a random guy you met at a party.

You will punch into the Amazon Life Timeline service “Go to when a met a man wearing a shirt with Sponge Bob on it”. You wait a few seconds and a video appears at the exact moment you met the guy at a party.

Our lives will be transparent, our ego will be lowered, because we as a species are happy to share and be transparent. We will tip towards transparency and away from privacy, why? Because if we do not, we create a stumbling block in our technological evolution. Data is king, and this is the fundamental reason why companies pay so much for apps.

Google is not a search engine, it is going to be the most powerful artificial intelligent service offering in the world. One day you will use Google’s AI to optimize your life. It will track how you drive, when you sleep, when you come home; and by doing so, will have enough data collection points to run AI routines on your data and provide you with awesome benefits.

Likewise, Amazon Machine Learning services will be our AI friend.

As programmers we going to need to store data about data or data about the bits that we send to the internet… Metadata.

One way to do so is by asynchronous messaging. You will of course have an App/Smart Device that needs to send data or metadata about user behavior.

Queue Sender

Your app can send small data messages as a user is consuming your service to an Amazon Queue on the cloud.

using System;
using System.Collections;
using System.Collections.Generic;
using System.Web;
using Amazon;
using Amazon.Runtime;
using Amazon.SQS;
using Amazon.SQS.Model;
using Amazon.Util;

namespace Wangle.Queue.Client
{
    public class AwsClient : IQueueClient
    {
        private AmazonSQSClient _client;
        private string defaultQueueUrl;

        public void Initialize(string url)
        {
            ProfileManager.RegisterProfile("Wangle", "myaccessKey","mysecretkey");
            var amazonSqsConfig = new AmazonSQSConfig { ServiceURL = "http://sqs.us-east-1.amazonaws.com" };
            _client = new AmazonSQSClient(ProfileManager.GetAWSCredentials("Wangle"), amazonSqsConfig);
            defaultQueueUrl = url;
        }

        public void SendMessage(string message)
        {
            var sendMessageRequest = new SendMessageRequest
            {
                QueueUrl = defaultQueueUrl,
                MessageBody = $"{message} + {DateTimeOffset.UtcNow}" //Unicode Only!
            };

            _client.SendMessageAsync(sendMessageRequest);

        }

        public IList<string> ReceiveMessage()
        {
            var data = new List<string>();
            var receiveMessageRequest = new ReceiveMessageRequest
            {
                QueueUrl = defaultQueueUrl,
                MaxNumberOfMessages = 10,
            };

            var receiveMessageResponse = _client.ReceiveMessage(receiveMessageRequest);

            receiveMessageResponse.Messages.ForEach(m =>
            {
                var receiptHandle = m.ReceiptHandle;
                data.Add(m.Body);
                _client.DeleteMessageAsync(defaultQueueUrl, receiptHandle);
            });
            return data;
        }
    }
}

Cloud Data Retention Receiver

Once the message is now in the message queue in the cloud, you will have a service in the cloud process this message and store it a Big Data Service. Below is the code to get the the message off the queue.

class Program
    {
        static void Main(string[] args)
        {
            //Fake a worker role service running in Amazon Cloud that processes data storage.
            Console.WriteLine("Fetching data logs from queue to prepare for governance...");
            var queueClient = new AwsClient();
            queueClient.Initialize(Settings.Default.QueueURL);

            while (true)
            {
                queueClient.ReceiveMessage().ToList().ForEach(m => Console.WriteLine(m));

                //ToDo: Store the audit data in AmazonS3 or Big Data service: User, Url, DateTimeUtc, SourceIP, DestIP
                Thread.Sleep(TimeSpan.FromSeconds(2));
            }

        }
    }

 

Summary

So that is basically the code you need. Of course you will need to install the Amazon Service SDK from Nuget.

This should get you going in the right direction when you need to send data to the cloud over the wire for later processing.

I am sure Amazon SQS will be used to start sending data asynchronously for  Fitbit information, how long you sleep for, how you drive your car and many more. Soon all our devices will be smart e.g. A cooking pot with a chip, your shirt with a chip …

See you soon in VR land…