Measurement is difficult to carry out in the agile engineering and management process. However, in practical activities, developers have been trying to use measurement to manage and monitor their own projects.
Measurement of software features helps developers to understand the software requirements consistently and completely, to know the actual quality extent and to make sure that the code is tested; For PMs, measurement process and product characteristics help them to understand whether the project schedule and cost is within the scope of the release time and budget projections; of course, customers have to go through the measurement, to test whether the final product meets demand with high quality. Maintenance personnel need the metrics to evaluate the current product, so that they can know how many efforts are needed in upgrades and improvement.
Some Scrum teams don’t agree that having metrics is an important factor in agile project management, but whether they agree or not, the metrics in agile projects is everywhere. On the other side, although a growing number of Scrum project teams recognize the historical data will help the project a lot, they wants to use the historical data to estimate and predict, most projects team don’t know what kind of metrics should be collected, or don’t know how to analyze the collected metrics, and how to use these metrics to guide their work.
In order to correct the misunderstanding about the metrics, and to help those who have realized the importance of historical data and want to use metrics to identify the problems, and find the root cause of the problem, improve the visibility of product and process performance, we should introduce the SPC – statistical process control to our Scrum project team.
This blog briefly talks about the situations which may lead to the difficulty of measuring a product’s quality.
Most of time, when producing a product such as an iPad, there are very detailed metrics that can be used to determine the product’s quality. For a project generating a software system, there should also be such detailed quality metrics in place when the project starts. Unfortunately, this is not always the case on some projects.
There are several possible situations where the quality cannot be measured effectively:
On a recent project, our GDC team was required to work on an independent performance testing project. Prior to the start of the project, we asked for any specific performance expectations from customer such as resource usage, response time, user load, etc. We were told that the customer didn’t specify that. As a result, we had to use test results of first time test execution as the benchmark. Typically, the benchmark should come from an existing live system provided by customer. In this case, the customer may forget to mention that but the BA should remind the customer to provide such data.
Usually, when planning a project, we need to think about one question: when should we stop testing? The answer to the question will lead to the quality gate of acceptance testing which can be further broken down into measurable quality metrics. However, there are situations where this has not been well defined for the project, which leads to a situation that the team has no idea when the testing should stop.
The missing of triage bar may also result in a situation where quality may not be measured properly. A typically project may define the pass of user acceptance testing as “no major or above defect”. However, if the triage bar (the description of blocker/critical/major/minor/trivial) has not been defined properly and shared within the team the quality of the product may not be fairly measured as well.
After read chapter 1 of book《Head First Statistics》, I found there are some good points about how to use different charts in reports. So I summarized below to share with everyone.
1. Pie charts are used to compare the proportions of different groups or categories. It’s usually easy to tell at a glance which groups have a high frequency compared with the others. Pie charts are less useful if all the slices have similar sizes, as it’s difficult to pick up on subtle differences between the slice sizes.
2. Bar charts are ideal in situations where categories are roughly the same size, as you can tell with far greater precision which category has the highest frequency. It makes it easier for you to see small differences.
Vertical bar charts tend to be more common, but horizontal bar charts are useful if the names of your categories are long. They give you lots of space for showing the name of each category without having to turn the bar labels sideways.
With a bar chart, it’s also easy to show multiple sets of data on the same chart.
The split-category bar chart: You can compare frequencies by showing related bars side by side. This sort of chart is useful if you want to compare frequencies, but it’s difficult to see proportions and percentages.
The segmented bar chart: You also can show proportions and total frequencies by stacking the bars on top of each other.
New Features for Web I
1. Linking
This feature allows you to filter the content of an element (a table or chart) related to a selection performed in another element (also a table or a chart). Simply select the element and using the contextual menu of your mouse, select the option « Linking / Add an element link». You can then specify whether one or all of the table’s dimensions will be used as selectors.In the example below, the year selected in the table on the left allows filtering of the data on the table on the right.First, for 2005 (figure 1), and for 2006 (figure 2).
While it was thought at one point that Web Intelligence would change its name to Interactive Analysis, it appears that it will keep its original name. But whatever what we want to call it, it has new features that will make you happy. To make your mouth water, here’s a preview of some features of SAP Business Objects 4.0 that will please every user.
New Features for BO 4.0
To be continued
Business analytic is hot in the trends (more people should know about the term of business intelligence or enterprise performance management)! GDC has a BI CoE(Center of Expertise) which is a group of engineers working and researching dedicatedly in the area of data discovery, data warehousing and data visualization etc. Every year we get new hires and graduates from campus to join this group therefore it’s mandatory to conduct formal training lessons and knowledge sharing sessions to newbie so as to help them know more about technical implementation and advanced analytic. I admit that it is actually a big world for various BI technology and products from different vendors. Sometimes, it may make the newbie confused on where to get started and I believe many folks have experienced that.
By leveraging our senior consultant experience and expertise in BI area, we launched the round table discussion for 2012. The objective of this kind of open discussion is to provide opportunities for both junior and senior people to expand their knowledge base, have brain-storming, as well as exchang opinions. The ground rules for this kind of technical salons are as followed:
In fact, the topics that we covered are broad – Gartner summit review, BI mobility, In-memory analytics, SQL server 2012, Informatica, Non-SQL (Hadoop) and others. Many of these technologies and products are emerging in recent years and we believe they will become main-stream in the near future. The first discussion about Gartner summit London review has been conducted by our colleagues and the form of activity is recognized by the participants whatever he is a new member or veteran.
As planned, in 2012 we will continue to pilot this open discussion program and hope most of our group members would gain maximum benefit from it.
Are you looking for a way which can help you to implement nice-looking and powerful table on you web page easily? Dhtmlx Grid probably is one of the best solutions you can consider. We have many success stories about using this component in various web projects.
DhtmlxGrid is an Ajax-enabled JavaScript grid control with cutting-edge functionality, power data binding, and excellent performance with larger datasets. It allows you to create a DHTML table with rich in-cell editing, resizable, sortable and draggable columns, built-in filtering, searching, and grouping capabilities.
At Xerox PARC, a company, they had a slogan: “Point of view is worth 80 IQ points.”
It was based on a few things from the past, like how smart you had to be in Roman times to multiply two numbers together; Only geniuses did it. We haven’t gotten any smarter, we’ve just changed our representation system. We think better generally by inventing better representations; that’s something that we as computer scientists recognize as one of the main things that we try to do.
I’m not sure if I have 180+ IQ points, but some point of views do effect the way I look at things in my daily work. These 2 videos are quite thought provoking:
Simplicity Ain’t Easy by Stuart Halloway
Simple is not compound
Most of the solutions in software we create are compound solutions, they are not simple. By understanding what’s simple and what’s compound, you will have a higher chance of creating simpler designs and solutions.
Simple Made Easy by Rich Hickey
Simple vs. Easy
Simple is the opposite of complex. A thing is simple if it has no interweaving, if it has only one purpose, one concept, one dimension, one task. Being simple does not imply one instance or one operation: it’s about interweaving, not cardinality. Importantly, this means that simplicity is objective.
Easy is the opposite of hard, or difficult. A thing is easy if it’s near to hand, if it’s easy to get at (location), if it’s near to our understanding (familiarity) or skill set or if it’s within our capabilities. This means that ease is relative.
Focusing on ease and ignoring simplicity means that you’ll go really fast in the beginning, but will become slower and slower as the complexity builds.
Focusing on simplicity will mean that you’ll go slower in the beginning, because you’ll have to do some work to simplify the problem space, but making sure that you only have intrinsic complexity means that your rate of development will remain at a high constant.
Recently I was talking with a friend who is running SMS Marketing activities against his CRM system. He came up with some ideas how to run it effectively. His company is a Chinese local baby products company that produces and sells formula milk, baby food, baby clothes etc. The ideas are to
Here, you can see “Optional Prompt” is dimmed as “False” and cannot be modified. It means the prompt is required to input value before running report. What if we set “Default Value” as blank and run the report?
Click on “OK”, the page does not respond. We are required to input a standard date value, e.g. 03/27/2012, before we are able to click on “OK” to proceed. So, the default value cannot be set as blank anymore for the prompt created within the Command Object, and the prompt cannot be optional.
I need to design a “Magic Date” value, something like January 1, 1900 as the placeholder. It is highly unlikely that any of my records will include that date as a valid entry. That is the first important point about this concept: I must pick a date that will never appear as part of my normal data. That is the magic date.
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