The industry is abuzz with the latest news announcing our release of the MissionKit Version 2011 Release 2. The release is loaded with new features for chart and report creation, enhanced data mapping capabilities, new XML Schema editing functionality, support for the latest version of BPMN, and a really cool new feature for comparing and merging Microsoft® Word documents. Dr Dobb’s and SQL Server magazine are just a few of the industry publications and blogs that covered the launch. Read what the industry is buzzing about and then download a free 30-day trial of the MissionKit and check out for yourself all the powerful new features now available in our suite of XML, database, and UML tools!
Tags: Altova, Altova XMLSpy, DatabaseSpy, MissionKit, StyleVision, v2011, v2011r2, XMLSpy
Altova first added support for charts and reporting the Altova MissionKit with the launch of Version 2011 last September. The v2011 reporting functionality includes options for line charts, 2D and 3D bar charts, 2D and 3D pie charts, round gauge and bar gauge charts. Here are a few examples:
Advanced chart features in v2011r2
Version 2011 Release 2 of the Altova MissionKit, introduced on February 16, adds an exciting group of enhancements to the chart and reporting features in XMLSpy, StyleVision, and DatabaseSpy. The chart design options and user interface work the same way in all three applications, so MissionKit users can work intuitively and productively as they move from processing XML data in XMLSpy, to preparing charts for a business intelligence report with StyleVision, and even when they create graphical displays directly from SQL query results in DatabaseSpy. The wide range of new customizable charting features introduced in version 2011 release 2 includes:
- Stacked Bar charts
- Area charts
- Stacked Area charts
- Candlestick charts
- Chart overlays
- Background images and color gradients
- Ability to change position of axis labels
- And more!
Now you can create attractive and informative charts to represent a wide variety of data sets without exporting data to a dedicated charting application. Charts created using the Altova MissionKit are not limited to any specific presentation technology – for instance you can use StyleVision to include charts in HTML, Microsoft Word, RTF, or PDF documents, or you can save charts created in DatabaseSpy in a variety of image formats at the custom resolution you specify. In this post we will show some examples of the new charts and features available in all three MissionKit reporting and charting applications – XMLSpy, StyleVision, and DatabaseSpy.
Stacked bar charts
Stacked bar charts are a variation on bar chart presentation and are especially useful when multiple ranges of data need to be illustrated. Stacked bar charts are also useful to more clearly illustrate data in a smaller area. The image below shows a stacked bar chart to illustrate the performance of a sales team by region over two years Note that the combined height of each stack in the Stacked Bar Chart represents the total sales over the two-year period for each Territory, since the sales for Last Year are added above the Year To Date numbers. Stacked bar charts complement regular bar charts and 3-D bar charts to offer users the greatest flexibility in illustrating SQL query results. If the user prefers horizontal bars, a checkbox labeled Draw X and Y exchanged in the Change Appearance tab selects that orientation. This orientation option is also available for other 2-D bar charts, line charts, area charts, and candlestick charts.
Area charts are similar to line charts, with shading applied to make a more graphically appealing display. The area chart below shows a record of temperature and humidity changes by hour over the course of one day. Creative application of color can emphasize the point! To successfully build an area chart, the analyst must consider the values in each data category. As the area chart is constructed, each category forms an opaque layer on top of the layers for data retrieved previously. In the case illustrated above, Temperature was always a larger number than Humidity, so a SQL query was constructed in DatabaseSpy to retrieve the Temperature value before Humidity to prevent Temperature from acting like a curtain to hide the Humidity data. However, if the data columns appear in a sequence with values in increasing order, the last layer would overlap and hide all the preceding layers. In that case, the chart tab heading titled Select Data lets the user add and delete columns from the results to re-sequence the data correctly. The Select Data column also lets the user edit the names assigned to each column on the X-axis label. As alternative solution, the Transparency option in the Change Appearance tab lets the user adjust color levels to allow hidden layers to show through.
Stacked area charts
As implied by their name, Stacked Area charts layer the columns of a data set to illustrate the overall sum of a data series. Stacked Area charts also eliminate the potential overlapping data problem that can occur with regular area charts. The chart below shows a table of air passenger revenue miles traveled by month, with individual regions for domestic and international travel. The Stacked Area chart creates a graphical representation of the total of Domestic and International miles, even though the total miles value was not part of the provided data. This is apparent at the top of the January entry, where the International region intersects the Y axis just below 600 (the original data showed 392 million Domestic miles and 181 million International miles, for a total of 573). A strategic data analyst will always consider the nature of the data to be reported when choosing any particular chart type. For instance in the weather example we used above, adding temperature and humidity values in a stacked bar chart would not be logical!
Candlestick charts were originally developed by a wealthy Japanese businessman who began trading at the local rice exchange around the year 1750. He kept records of the local market psychology, learning to boost his profits by carefully monitoring prices and not rushing into trades. Today, charts are used to represent financial data such as stock prices over a period of time. Every day the market is open, each stock has four relevant data points that can be rendered in a candlestick chart: the price at market opening, the price when the market closed, the high price during the day, and the low price during the day. Investors and financial analysts like to view these indicators to gauge the stock’s performance over a period of time. In the candlestick chart below, each solid bar represents the range between the opening and closing price and the thin vertical line through each bar shows the extent of the high and low prices for the day. In this version of the chart, following common convention, the color of each bar signals whether the stock was up or down for the day. If the bar is green, the stock was up for the day– it opened at the price indicated by the bottom of the bar and closed at the price indicated by the top. If the stock was down for the day, the bar is red and the symbolism is reversed – the stock opened at the price indicated at the top of the bar and closed at the price shown by the bottom. Numerous options are available to set line and fill colors, the Y-axis range and values, and more. Because they were intended to be printed in black and white, the original candlestick charts used empty bars to indicate the price increased and solid bars to indicate price decreases. The Altova MissionKit offers this option: Another candlestick chart variation omits the opening price and simply illustrates the range by a vertical line and the closing price by a horizontal line. This option is automatically supported when a data set only includes the high, low, and closing prices.
The Overlays feature lets you combine multiple charts in a single image. Each overlay chart has unique settings and can even be generated from a separate data file. The image below shows a candlestick chart of a stock’s daily prices with the daily sales volume in a bar chart overlay.
Support for background images & color gradients
The ability to specify background color gradients and background images gives you even more flexibility for creating customized, eye-catching charts. Overlaying one chart on another lets you visualize multiple data sets with different Y-axes and types. The Change Appearance dialog lets users select a background image, as in the Winter Games chart above, or apply a background color gradient, as in the Summer 2010 chart below. If you’d like to see for yourself how easy it is to use Altova tools to create attractive charts from XML and database data, download a free trial of the Altova MissionKit.
Tags: altova product upgrades, charts, MissionKit, v2011r2
We’re pleased to announce the availability of Release 2 of Altova’s 2011 product line, which adds numerous new features to our entire MissionKit tool suite, as well as all standalone products. Even though it’s been just five short months since Version 2011 was announced, Release 2 packs a formidable punch, delivering innovative new features to meet customer requests and provide the unique, advanced functionality you’ve come to expect in the award winning MissionKit. Below are a few details on Release 2 of the Altova MissionKit 2011. For complete information and screenshots, click over to the Altova What’s New page. Subsequent posts over the next few weeks will cover each product and each feature in more detail. Advanced Chart and Report Creation The new functionality added in the MissionKit 2011 for creating charts and reports to analyze database, XML, XBRL, and other types of data received some important updates in Release 2, including new chart types, new formatting options, and more. New chart types add to the long list already available and include area charts, stacked area charts, candlestick charts, and more. You can add even more advanced formatting options to your charts now, using background images, color gradients, and variable axis label positions, as shown in the stacked area chart below. R2 also adds support for chart overlays, which combine two disparate sets of data in one chart, as shown below. This example combines a candlestick chart of a stock’s daily prices with the daily sales volume indicted using a bar chart. These new charting and reporting tools add to those already available in XMLSpy, StyleVision, and DatabaseSpy, providing multiple opportunities to visualize, analyze, and report business data in innovative ways. Other v2011r2 Highlights R2 includes a lot more than just new chart and report creation features. We’ve got some great new tools for XML Schema editing in XMLSpy, as well as fully customizable documentation generation for XML Schema, WSDL, and XBRL via StyleVision integration. MapForce provides several enhancements for data mapping, such as enhanced ETL performance through data streaming, support for the IATA PADIS EDI format, and more. StyleVision now supports barcodes and other new tools for advanced report creation and publishing. BPMN support in UModel has been updated to the latest version, 2.0, and you can also now generate code from State Machine UML diagrams. And finally, just when you thought the DiffDog diff/merge tool couldn’t be any cooler, we’ve added full support for comparing and merging Microsoft® Word docs (yes, it’s actually easy to use). All these new features are expanded on here and will also be covered at length in upcoming blog posts. Make sure you are subscribed to the blog or our Facebook page, and do check back often for updates!
Tags: Altova, Altova XMLSpy, DatabaseSpy, DiffDog, MapForce, MissionKit, SchemaAgent, software tools, StyleVision, technology books, UModel, XML Editor, XMLSpy
Authors of various industry reference books ranging from SOA and Web services to XML continue to use and recommended Altova tools. The latest update to the Cold Fusion book series – “ColdFusion 9 Developer Tutorial” is an update to John Farrar’s “ColdFusion 8 Developer Tutorial”. In this latest update, Farrar uses the Altova MissionKit, our suite of XML, database, and UML tools to do all his XML work for the book. According to Farrar, “I have a suite of tools from Altova and find they do what I want. I can create XPath, XML Schemas, and more from their tools and don’t ever feel the need to look for a new tool.” Farrar, a ColdFusion expert, teaches the basics of ColdFusion programming, application architecture, and object reuse. He then shows off a range of topics including AJAX library integration, RESTful Web Services, PDF creation and manipulation, and dynamically generated presentation files. So whether you need an overview of XML technologies, the latest information on working with ColdFusion, or want to delve into Web services, you’ll want to check out the Altova Reference Books page on our Web site.
Tags: cloud services, DatabaseSpy, MissionKit
Working with Altova Tools and the Amazon Relational Database Service (Amazon RDS)
More and more enterprises are discovering the advantages of implementing database applications in the cloud:
- High availability and reliability
- Automatic scaling
- Freedom from hardware costs and maintenance requirements
In this blog post we demonstrate how to connect to the Amazon Relational Database Service (Amazon RDS) and build a small database using Altova DatabaseSpy. Since the database Connection Wizard is consistent across the Altova MissionKit, you can connect the same way using XMLSpy, MapForce, or StyleVision. If you would like to follow the steps described below for yourself, you will need to sign up for an Amazon Web Services (AWS) account at: http://aws.amazon.com/rds/ You can also download a fully-functional free trial of the Altova MissionKit or any individual Altova application at: https://www.altova.com/download-trial/
Build a Local Prototype
The Amazon RDS is based on MySQL, so we will build a small local database in the MySQL Community Edition, then migrate to the Amazon RDS and test our database in the cloud. Although MySQL does not support XML as a data type for database columns, MySQL 5.1 and 6.0 do support some operations for XML data stored as text. For this exercise we will adapt and extend some of the MySQL XML examples at the MySQL reference resources listed here: http://dev.mysql.com/doc/refman/5.1/en/xml-functions.html http://dev.mysql.com/tech-resources/articles/xml-in-mysql5.1-6.0.html http://dev.mysql.com/tech-resources/articles/mysql-5.1-xml.html First, we launched DatabaseSpy and connected to our local MySQL Community Edition. We created a new data source named LocalPrototype, and created a new database schema that we named XMLtest. The DatabaseSpy Online Browser and Properties windows are shown here: Next, we created two tables called books and cities and inserted data by following the examples in the MySQL documentation. Here is a DatabaseSpy Design View of our tables: We can run select queries and display the contents of our tables in stacked results windows: Note that the doc column of the books table contains XML data, although it was defined as varchar(150). MySQL supports two functions for working with XML in text fields, ExtractValue() and UpdateXML() that can operate on individual elements via XPath expressions. Below is a simple ExtractValue() query to return only the author initials from every row in the books table: The UpdateXML() function can be used to modify the contents of individual XML elements using a SQL expression. In the screen shot below, the query on line 1 updates the every row of our books table, and the query on line 2 returns the new values: We can also use the Concat( ) function to add XML elements to non-XML data such as the cities table, as shown below: So far, our XML queries have operated on all rows of each table. To facilitate queries for a single row, it’s handy to add a column top the table to hold a unique row index. We can make a copy of our books table and add a column called id to hold the row index. The id column also makes a convenient foreign key to reference an individual XML document in our table from a row in another table. For instance, you might define one table to contain names of job candidates, with a foreign key to reference the XML-formatted resume for each candidate, stored in a separate table. You can use the SQL Editor in DatabaseSpy to generate a CREATE statement for the existing books table and edit it directly, or you can use the DatabaseSpy Design Editor to build the table graphically. (For more information, see the DatabaseSpy section of the Altova Web site.) Since we are planning to run the same queries later in the Amazon RDS, we combined a SQL CREATE statement and SQL INSERT statements into one script for the books2 table. The screen shot below shows part of the script for books2: We can run a query of the books2 table that shows the unique id column for each row: Now we can enhance our UpdateXML() and ExtractValue() queries to act on an individual row: This gives us a good baseline set of examples to take to the cloud and test in an Amazon RDS.
Connect DatabaseSpy to the Amazon RDS Cloud
After you follow the instructions at the AWS Management Console to create a database instance on Amazon RDS, the Connection Wizard makes it easy to get started with DatabaseSpy. Simply choose the MySQL option as shown here: The first time you connect, you will need to create a new DSN. After the first time, you will be able to select the DSN from a list by choosing the “Use an existing Data Source Name” option. You can even use the original DSN when you go back to connect from XMLSpy, MapForce, or StyleVision. In the connector dialog, fill in the following information:
- Data Source Name: This is the name that will be listed in the DatabaseSpy Project. window and in the list of existing data sources when you connect again.
- Description: Information for your own reference.
- Server: This is the Endpoint name listed in your Amazon RDS account dashboard.
- Port: 3306 – make sure your IT department isn’t blocking this port with a firewall!
- User / Password: This is a user you set up in Amazon RDS.
- Database: The default database name you configured when launching your RDS instance.
We connected to our Amazon RDS cloud database in the same DatabaseSpy project we built for the local prototype. Here is a screen shot of the project window showing both Data Source Names and the working SQL files we added to our project: Before we build our tables and run the queries, it will be interesting to check the versions of each system. The screen shots below show a query that requests version information for each system. Note that the gray bar directly above each query indicates which data connection the SQKL statement is assigned to. The Amazon RDS reports it is running version 5.1 of the MySQL Community Server, the same as our local prototype – a promising omen!
Migrate the Local Project to the Cloud
We can open each of our original table creation scripts and run them in the cloud database by re-assigning the execution target in the Properties window: The gray Execution Target bar near the top of the SQL Editor window identifies the cloud Amazon RDS database as the query target: After similarly creating the books and books2 tables, we can run each of the SQL queries in the cloud database. ExtractValue() function for all rows example: Concat() query to create XML output from non-XML data in a table: UpdateXML() example for a single row in a table. ExtractValue() for a single row:
In every test we performed, Amazon RDS behaved exactly like the local MySQL community edition. This behavior it much more efficient for developers to build and test new cloud database applications, or enhancements to existing applications, without incurring the cost of cloud resources for development iterations. We also verified the operation of MySQL XML functions for XML data stored in text columns in the cloud databases. Our XML data was very limited – the text column in our books table was limited to 150 characters. However, MySQL lets you store much larger XML documents in a single column. Every table has a maximum row size of 65,535 bytes. Even if your table uses an index column, this means a varchar column for one XML entry could be over 64k bytes. If you need to store even larger XML documents, MySQL offers MediumText and LongText data types, similar to BLOBs. MediumText can hold over 16 million single-byte characters and LongText can hold up to 4 GB. Although not illustrated in this blog post, we have successfully tested ExtractValue() and UpdateXML() functions with MediumText and LongText data types. When you need to store XML data files that large, writing XPath expressions to resolve individual elements can become a development challenge. The XPath Analyzer included with XMLSpy is an invaluable tool that facilitates the testing and debugging of XPath 1.0 and 2.0 expressions. As you type an XPath expression into the analyzer, XMLSpy evaluates it and returns the resulting node set in real time. This can save hours of debugging time spent trying to understand and track down XPath problems. In future blog posts we’ll explore other ways XMLSpy, MapForce, DiffDog, and DatabaseSpy can help developers accelerate creation of cloud application with Amazon RDS. We look forward to seeing you back soon! If you’d like to see for yourself how well Altova tools work with Amazon RDS, download a free trial of the Altova MissionKit.
Tags: Altova, DatabaseSpy, DiffDog, Japanese Versions, MapForce, MissionKit, software tools, StyleVision, UModel, Version 2011, XML Editor, XMLSpy
With the release of Version 2011 we are thrilled to bring you the Altova MissionKit in Japanese. Now all the Altova tools available in the MissionKit have been fully translated into Japanese. Like the English and German versions of the tool suite, the fully translated Japanese language version provides users with powerful functionality for XML and Web development, data mapping and integration, rendering and publishing of XML, XBRL, and database data, UML modeling, and more. All the tools available in the new Japanese language version of The MissionKit are available at the same cost as the English versions, and current Version 2011 users can now unlock any language version using their existing key code. If you haven’t checked out our latest release – Version 2011, download a free, 30-day trial today! The Japanese language version of all the MissionKit tools can be purchased from the Altova Online Shop or through your preferred reseller.
Tags: Altova, Award, MissionKit, renewable energy, Version 2011
We are proud to announce that Altova was selected for the “2010 Best of Beverly” award in the Computer Software Development category by the U.S. Commerce Association (USCA)! The USCA “Best of Local Business” award program recognizes outstanding local business throughout the country and each year identifies companies they believe have achieved exceptional marketing success in their local community and business category. We are proud to be recognized by our local community for our success in the software industry as well as for the contributions we’ve made to the local area, such as committing to use renewable energy. And be sure to check back often to learn more about what we’ve been up to, including the most recent software release – Altova MissionKit Version 2011 – to helpful Tech Notes, the latest industry buzz, and other Altova awards.