Tim Berglund

Presentations

Practical Agile Database Development

Do your team's agile practices extend to the database? Agile methods are fairly well-understood as they apply to code, but these principles are not commonly understood or practiced on the databases that typically accompany enterprise software projects. Learn the tools, techniques, and mindset your team needs to make incremental improvements to the database’s design over time with confidence.

We'll cover Scott Ambler and Pramod Sadalage's vision of database agility as described in their book Refactoring Databases. We'll discuss the five-pointed constellation of evolutionary design, refactoring, automated testing, source control, and developer sandboxes, and how each of these practices contributes to successful database development. In particular, we'll look at how these practices are enabled by the open-source tool, Liquibase. We'll study a database badly in need of reform, select some refactorings from Ambler's catalog, and implement them in real time in a way that can satisfy the development team and the maybe even the production DBAs! This tool and the practices that animate it produce real results, cleaning up an area of development that is all too often left messy and uncontrolled. If there is a relational database in your life, you will benefit from this talk.

Complexity Theory and Software Development

Some systems are too large to be understood entirely by any one human mind. They are composed of a diverse array of individual components capable of interacting with each other and adapting to a changing environment. As systems, they produce behavior that differs in kind from the behavior of their components. Complexity Theory is an emerging discipline that seeks to describe such phenomena previously encountered in biology, sociology, economics, and other disciplines.

Beyond new ways of looking at ant colonies, fashion trends, and national economies, complexity theory promises powerful insights to software development. The Internet—perhaps the most valuable piece of computing infrastructure of the present day—may fit the description of a complex system. Large corporate organizations in which developers are employed have complex characteristics. In this session, we'll explore what makes a complex system, what advantages complexity has to offer us, and how to harness these in the systems we build.

Gaelyk: Cloud-Based Apps With Groovy

You love Groovy and you're a believer in cloud computing. For a larger project you might choose Grails and hosting on Amazon EC2, but what if you want to take advantage of the nearly massless deployments of a cloud provider like the Google App Engine? You could make Grails work, but it's not always the best fit. Enter Gaelyk.

Gaelyk is a lightweight Groovy web application framework built specifically for the Google App Engine. In this session, we'll talk through the simple abstractions it offers, then show how easy it is to code and deploy a useful application to the cloud.

Open Source Business Intelligence - Part I

Traditionally, business intelligence tools have been a high-cost part of any enterprise's software inventory. Recently, options have emerged that allow architects to build a credible business intelligence stack out of entirely open-source components. In this brief overview, we will demonstrate ETL, reporting, and analytics tool that can be deployed free or at low cost. Learn how to turn your company's transactional database into a rich data asset with a business-friendly user interface that integrates into your existing software infrastructure.

We begin this session talking about the differences between a transactional database and a data warehouse, describing the many benefits of creating the latter. Then we'll take an actual transactional database and show how to convert it into a warehouse star schema using the Eclipse-based Talend ETL. Next, we'll demonstrate how to enable business analysts to build reports with Jasper iReport, an open-source visual report designer. We'll talk about ways to integrate these report designs into your Java- or Groovy-based application. Finally, we'll look at more sophisticated options for analysis using tools from Pentaho.

This is a mile-wide, ankle deep view of an open-source business intelligence stack. Through this whirlwind overview, you'll learn the basic principles of business intelligence, how to think architecturally about the components of a BI stack and how to integrate them into the enterprise, and what specific tools you can employ to get the job done.

Open Source Business Intelligence - Part II

Once you're familiar with the concepts of data warehousing, star schemas, cubes, and pivot tables, then it's time to dive in and look at how the tools really work. Continuing from the quick demos in Part I, in this talk we'll walk through the process of transforming a transactional database into a star schema, then we'll use an open-source analytics tool to build a "cube" with that schema. Concepts and procedures gently introduced in Part I will be explored more thoroughly, and new tooling will be introduced.

After we've built and run a functioning ETL job and published our star schema to the Pentaho Analytics Platform, we'll briefly introduce ourselves to Weka, an open-source data mining platform. Data mining complements reporting and analytics tools by allowing us to harness pattern matching algorithms and machine-scale data processing speeds to find otherwise obscure patterns in large datasets. With a solid grasp of the entire BI stack, no data set need be beyond your analytical grasp.