Web Components are Real

Web Components are not another internet buzzword. Web Components are a collection of web browser constructs and standards that will modernize client side web development and improve the web design process overall. This is a long time in the making, but these are the missing building blocks (along with continued ECMAScript maturity) that are needed to bring web development on par with traditional structured programming languages and environments without the need the crazy hacks we have today.

The key standards behind Web Components include:

• Shadow DOM: Finally DOM trees that don't step on each other. Modular DOM structures can exist and interact with each other.
• Custom HTML Elements: HTML building blocks where each custom element can have encapsulated properties functions and events. Elements can exist in a hierarchy/nesting and look and act like native HTML elements.
• HTML Imports: Import HTML pages and source files like other programming languages.
• CSS Grid Layout: Table and grid layout done in a more intuitive way and more akin to how most client GUI frameworks handle widget layout.

These standards will impact low level frameworks such as jQuery, but will also change the way higher order client side frameworks like AngularJS, GWT, Ember, Knockout evolve over time and how they provide wiring, plugin and extension capability to their developers.

So get ready for Web Components. They are real and will finally bring modular and structured web programming to the web to support more robust, scalable and maintainable, extensible client side development frameworks.

P.S. Keep an eye on the Polymer project if you want to experiment with Web Components today. This client side framework, packages many of the emerging standards into a developer friendly API and programming model. But keep in mind that Polymer is not Web Components, it is just a project that demonstrates the power of these new Web Component standards.

JobServer Release 3.6.14

We are happy to announce the release of JobServer 3.6.14 which introduces LDAP support and improved shell script processing to allow turning any standalone program or shell script into an easy to automate and track application. Yes, with JobServer you give your shell scripts and batch standalone programs a GUI front-end that you can use to customize your shell scripts and leverage powerful reporting and monitoring to easily track all input and output related to your batch scripts and standalone programs.

With this release, JobServer now supports improved tracking of shell script output via the JobServer JobTracker reporting and tracking application. You can now preview the standard output of every shell script right from the top level JobTracker search report. You can also now run shell script jobs manually and pass custom input parameters to the shell scripts. Using JobServer with batch scripts just got a whole lot more fun and productive.

Want to simplify user authentication for you and your JobServer end users? Now with LDAP support, you can integrate JobServer with your Active Directory and LDAP compatible environment for more seamless user authentication.

Download and test drive JobServer 3.6.14 today and learn more about JobServer's powerful developer SDK, soafaces, that makes extending and customizing JobServer and developing custom jobs and backed automated services easier.

Grand Logic delivers software solutions that automate your business processes and tame your IT operations & Big Data analytics. Grand Logic delivers data and job automation software, Hadoop and predictive analytics consulting services that maximize your Big Data investment.

Tableau for Agile Oracle Essbase Financial Reporting

Oracle Hyperion Essbase is an established multidimensional database platform often used by accounting departments to model and store their company's financial data. Essbase comes with out of the box Oracle web reporting utilities to help you visualize your financials for management and also comes with integration with tools such as MS Office for reporting via Excel.

In the traditional desktop Excel world view, you end up passing around lots and lots of excel spreadsheets and statically built PDF reports around your organization and with your executives - a bit antiquated in this day and age to say the least. You will however find that Excel, to its credit, is commonly used to build fairly advanced reports with Essbase using home grown Excel and VB programming. But there has to be a better way that does not involve building complex data warehousing, ETL and using outdated BI visualization tools.

Now Tableau is a fast growing and popular visualization BI solution that enables business analysts (without advanced technical expertise) to perform data discover and build rich and sophisticated visualizations that can be more easily shared than traditional Excel spreadsheet sharing. Tableau has emerged as a powerful replacement for Excel based reporting and a challenger as well to the established enterprise BI platforms such as Microstrategy and Cognos to mention a few. Tableau fits well as an agile replacement for Excel reporting while allowing users to build very powerful next generation reporting and dashboards that outperform the traditional enterprise BI vendors in agility and visualization capabilities.

Tableau still has a way to go on the enterprise end, but it is coming on strong and if you know how to deploy and implement Tableau Server you can build highly agile and visually rich enterprise grade BI solutions. For financial reporting, Tableau allows you to take your legacy Essbase reports and spreadsheets out of the dungeon and into the light of day by allowing you to build sophisticated dashboards that can be easily accessible across your orgaization via Tableau Server by all your executives.

With Tableau you can just say no to having to build yet another data warehouse and complex ETL when architecting your business intelligence strategy. But be aware, Tableau can be used to extract data from Essbase directly using the built-in Tableau to Essbase connector, but say no to this approach. The Tableau Essbase connector will not work (needs another blog). We strongly suggest not using the Tableau Essbase cube connector for a number reasons (not all Tableau related). This connector has many challenges. A hint - extract your Essbase data using the Essbase Excel plugin and mix with a little ETL and output to denormalized flat data structures. Say what? Yes this approach rocks! Remember that Tableau is great at extracting dimensionality out of your data (that is one of its claims to fame actually).

At Grand Logic, we have developed an elegant and straight forward approach to extracting data from Oracle Essbase for agile and efficient consumption by Tableau. This in turn can be used to build advanced financial reports and dashboards without a huge investment in data warehousing and ETL processing. Our approach to integrating Tableau with Oracle Essbase leads to a powerful solution that will leave your executives wanting more and frees your accountants and financial analysts from building cumbersome to maintain Excel reports. Get your financial reporting and dashboarding in Tableau today for centralized access and in an environment governed by one version of the truth. Put actionable and insightful data in the hands of your executives.

Are you also looking to invest in Big Data infrastructure and analytics? Essbase does not have to be an isolated island of data divorced from your Big Data initiatives. Read more on how you can integrate Essbase data with your Big Data analytics.

Looking to get your Essbase cube into a Big Data lake? Learn more how you can integrate Essbase with Tableau and Apache Spark to supercharge your Tableau and Essbase connectivity.

Tableau and Essbase can be a great combination for building rich reporting and dashboards and without the overhead and complexity of traditional data warehousing and BI. Get your financial data out of Essbase and into Tableau and into the hands of our executives and decision makers. Contact Grand Logic to learn more.

Machine Learning: The Brains Behind Big Data

The first round of the data revolution has focused around commoditizing computing and storage. Platforms such as Hadoop and NoSQL have helped to propel this and have enabled businesses to economically deploy more powerful scale out infrastructure than before. It has also changed and improved the way data warehousing and business intelligence is approached and managed. The storage and performance capabilities of Big Data have been a game changer. Traditional descriptive BI and reporting will never be the same. But this is just step one. The best is yet to come.

The industry is now going through a learning processes with how to manage all this data at massive scales. Storing and managing more data is great, but people and businesses will get smarter at how much data to keep as it starts to hurt more (hurt the pocketbook). How much data you keep and mine will depend on statistically driven best practices and not just about data warehousing or how big your HDFS cluster is. The mainstreaming of Big Data has provided the muscle to store and process massive amounts of data at near linear scale, but we will not see the real value of all this Big Data storage and processing until machine learning and data science tools become more assessable (to the non-PHD data scientists among us) and mainstream and businesses learn how to apply these tools and disciplines effectively.

Machine Learning will provide the brains to go along with the Big Data muscle. In the long-run businesses will decide how much data to keep around based on statistical measures and best practices as they grow to understand their data and their business better as they build out developing their predictive and prescriptive analytics.