Big Challenges in Data Modeling: NoSQL and Data Modeling
 

Big Challenges in Data Modeling: NoSQL and Data Modeling

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Big Data and NoSQL have led to big changes In the data environment, but are they all in the best interest of data? Are they technologies that "free us from the harsh limitations of relational ...

Big Data and NoSQL have led to big changes In the data environment, but are they all in the best interest of data? Are they technologies that "free us from the harsh limitations of relational databases?"

In this month's webinar, we will be answering questions like these, plus:

Have we managed to free organizations from having to do Data Modeling?
Is there a need for a Data Modeler on NoSQL projects?
If we build Data Models, which types will work?
If we build Data Models, how will they be used?
If we build Data Models, when will they be used?
Who will use Data Models?
Where does Data Quality happen?

Finally, we will wrap with 10 tips for data modelers in organizations incorporating NoSQL in their modern Data Architectures.

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Big Challenges in Data Modeling: NoSQL and Data Modeling Big Challenges in Data Modeling: NoSQL and Data Modeling Presentation Transcript

  • YourModerator Karen Lopez Sr. Project Manager / Architect Infoadvisors @datachick #BCDModeling JoiningKaren Dan McCreary Principal Kelly-McCreary & Associates @dmccreary
  • NoSQL And Data Modeling Big Challenges in Data Modeling
  • Making Sense of NoSQL clearly and concisely explains the concepts, features, benefits, potential, and limitations of NoSQL technologies. Using examples and use cases, illustrations, and plain, jargon- free writing, this guide shows how you can effectively assemble a NoSQL solution to replace or augment the traditional RDBMS you have now.
  • Data Models – Traditional Process Conceptual (Data) Model Logical Data Model Physical Data Model(s) OLTP OLTP OLTP OLTP OLTP MARTMART OLTP OLTP OLTP
  • NoSQL Data Store Types • Key Value • Graph • Columnar • Document • XML • ….more?
  • Traditional Data Modeler Involvement Project Initiation Architecture and Infrastructure Design SW Requirements Development Deployment
  • Modern Data Modeler Involvement Project Initiation Architecture and Infrastructure Design SW Requirements Development Deployment
  • ETL EDW Data Mart Data Mart
  • Hadoop ETL EDW Analytics Mart Data Mart
  • “Every design decision should include cost, benefit and risk” • - Karen Lopez
  • 10 Tips For Modeling in a Hybrid World 1. Models require a modeler 2. Data modeling tools are essential – choose wisely 3. There are many types of data models: know which ones you need 4. Modeling does not have to happen at the same time in every project. It should happen at the right time 5. Modeling is not just schema design. Think outside the boxes and lines
  • 10 Tips for Modeling in a Hybrid World 6. A data model is much more than a diagram 7. You will need training. More than you think. 8. Team members may not understand modeling. They will need training 9. NoSQL is not one thing. Learn many patterns 10.Modern data architectures are likely hybrid solutions. You can’t just support one part.
  • This book is written for anyone who is working with, or will be working with MongoDB, including business analysts, data modelers, database administrators, developers, project managers, and data scientists.
  • See you 24 July Big Data - Myths, Misunderstandings and Mistakes Thank you! Karen Lopez @datachick