We have added a new section to the site, Publications, under which you can find journal papers, referenced articles and omitted appendixes. All presentations made at various conferences can also be found here, along with scripts for setting up and testing Anchor Modeling.
This should make it easier to find reference material, which previously you had to scan old blog posts to find.
Lars Rönnbäck will be going to HAN (Hogeschool van Arnhem en Nijmegen) in the Netherlands to hold lectures on Anchor Modeling between June 28th and July 1st. For more information, visit the event registration page at HAN by clicking here. The week will open with a free guest lecture in which Lars will introduce Anchor Modeling, followed by a comparison of Anchor Modeling and Data Vault by Martijn Evers. The program for this day can be found by clicking here. Between June 30th and July 1st a two day crash course will be held in which participants will, among other things, build their own models and learn the details of Anchor Modeling. Applying for the course can be done by clicking here (with an early bird rebate until May 22nd). Note that all courses and lectures will be held in English. Below is the course description in English.
Crash Course in Anchor Modeling
Information is volatile. The frequency with which changes to both structure and content occur is rapidly increasing, and previous modeling techniques are not fit to handle this new and turbulent environment. Anchor Modeling is an agile modeling technique specifically designed for coping with information the evolve over time. In Anchor Modeling a model is not built to last – it is built to change – only then can it truly last in an ever changing environment.
Day 1: (basic modeling)
- motivations and philosophy for a new modeling technique
- a brief history of Anchor Modeling
- positioning Anchor Modeling against other techniques
- the Anchor Modeler, an online modeling tool
- the four basic building blocks
- information historization
- conceptual modeling
- naming convention
- modeling guidelines
- natural and surrogate keys
- physical implementation (tables, views)
Exercise (Anchor Modeler): building your own conceptual model
Day 2: (under the hood)
- XML representation
- generated SQL code
- performance implications
- hardware and database support
- indexing in Anchor Modeling
- table elimination (outer and foreign)
- three constructions for modeling time
- simultaneous information, default values, multi-language
- evolving a model
- evolving a database without downtime
- loading data into a model
- zero update strategy
- benefits of Anchor Modeling
Exercise (Anchor Modeler + Microsoft SQL Server): implementing your model in a relational database
In preparation for the course, Microsoft SQL Server 2008 R2 Express (free with a 10GB database size limit) can by downloaded by clicking here.
The online modeling tool has been extended with new functionality that keeps a history of how the anchor schema has evolved over time. In Anchor Modeling all previous schemas are available as subsets of the current schema. Now, using this new functionality all previous schemas are also accessible through the _Schema table. On top of this table four views have been added that shred the XML of the schema into rows and columns: _Knot, _Anchor, _Attribute, and _Tie, through which details about the tables can be followed over time. A utility function, _Evolution(@timepoint), that compares the tables in the current database with the schema that was in effect at the given @timepoint is also available. To see this in action, please watch our new tutorial available in our Tutorials section, or by clicking here.
We will be speaking about Anchor Modeling in a presentation named “New trends in data modeling” at the GSE Nordic Region Conference, 2011 (7-9 June), in Stockholm, Sweden.
Here is an excerpt from the abstract:
We need to rethink the concept of a data model. We live in a world where the available information changes more rapidly for every day that passes. This is true both for the content and structure of the information. On top of that, search requirements are also becoming inherently harder to predict. In such a turbulent environment, current data models do not stand the test of time…
We have added some new tutorials that highlight recent features in the anchor modeler (the online Anchor Modeling tool). Among these are the naming convention and how the tool enforces this, context sensitive keyboard shortcuts for modeling operations, and a discussion on the layout algorithm and some of the options affecting it. You can find them under the “Tutorials” menu, or by clicking here.
Due to a change in the Google App Engine backend for handling logins, the Anchor Modeler is currently unable to connect to the cloud. We expect to have fixed this early next week. We apologize for any inconveniences this may cause.
Update March 7, 2011:
The issue has now been resolved.
We are happy to announce that our journal article has been published in the December 2010 Special Edition issue of Data & Knowledge Engineering. The final version of the paper can be found by clicking here.
A guest lecture has been held at DSV, Stockhom University, for the Data Warehousing class. This year the lecture was split over two sessions in which the basics of Anchor Modeling was covered. The online modeling tool was also introduced and an assigment was given to the students in which they will create a simple model. In other words, close to 200 students will help out with the testing of the tool.
The Anchor Modeler (http://www.anchormodeling.com/modeler) is now connected to the Cloud for loading and saving models. Models can also be saved as “public” and become viewable by everyone. The connection to the Cloud is done using Google’s App Engine, so all you need is a Google account to use it. Come share your models!
We are happy to announce that our journal article “Anchor Modeling – Agile Information Modeling in Evolving Data Environments” for the Special Edition Issue of Data & Knowledge Engineering has been accepted for publication. A preprint of the article can be read by clicking here.
Maintaining and evolving data warehouses is a complex, error prone, and time consuming activity. In order to support the design and maintenance of data warehouses, we have developed a novel information modeling technique, called Anchor Modeling. A key benefit of Anchor Modeling is that changes in a data warehouse environment only require extensions, not modifications, to a data warehouse. This makes it possible to iteratively model and apply fragments of a data warehouse, which supports agile ways of working. Furthermore, Anchor Modeling results in databases that in many situations perform substantially better than databases constructed using traditional modeling techniques.