Posted by Max Ziff, Engineering Lead, Google Enterprise Team

Enterprise Content Management (ECM) systems are useful to manage and version control the information assets of the organization. But lets be honest, they don't necessarily have the most best search mechanism to retrieve the valuable information contained within. The default search capabilities provided by ECM systems create new silos where users must log-in to multiple applications to retrieve the information. Our mission at Google is to provide a unified search experience across all enterprise content sources. Due to technical differences in the interfaces and the different security mechanisms supported by ECM systems there is need to build specific connectors to these systems.

We just open-sourced an interesting project that will make it easy to build connectors to ECM systems. This new connector framework provides rich service provider interfaces (SPI) to write connectors to different content sources. It also provides a security infrastructure to securely index and serve documents stored in ECM systems. Finally it provides rich administrative capabilities to configure the connectors to different ECM systems in a centralized way. The connector framework is designed for building connectors to ECM systems as well as other content sources that may or may not have web-enabled content.

The open source project contains source for Connector Manager, Connector SPI interfaces, associated javadocs, sample code and test suites. This is an early technical preview of the connector manager project and is not (yet) an officially supported feature in the Google Search Appliance. We wanted to get the word out sooner and invite the broader developer and partner community to give us feedback. Check out the connector manager project and let us know your thoughts on it.

Posted by Dave Girouard, VP and General Manager, Google Enterprise

Our OneBox technology has been part of our Search Appliance product since last April and it's really taking off with our customers. We're constantly hearing about cool and interesting uses of the technology for integrating realtime data into enterprise search results, just like weather forecasts can be integrated into Google.com results. One sly Google engineer connected our internal search appliance to a database of Googler's license plates, thus greatly easing the process of finding that sad soul who left their headlights on, blocked somebody else in, or was sideswiped by a runaway Prius. Just type in "plate" followed by any series of numbers or letters and you can immediately drop a message to the car's owner.

Posted by Kevin Gough, Enterprise Product Manager

Lakehead University became our first large-scale deployment of Google Apps for Education in Canada and shared with us some truly impressive statistics. Lakehead transitioned 38,000 students, faculty and alumni to Google Apps for Education in just one week. We think that getting all three of these groups on the same collaboration system should have a huge impact on learning (and student social calendars) as well as keep alumni involved in the campus community. Users should be excited about going from 60 MB of storage on their prior email system to 2 GB with Google Apps - eliminating the need to delete those large project files that happen to become useful come finals time.

What's most impressive is that Shahzad Jafri, Lakehead's Chief Information Officer, estimates that Lakehead will save $2-3 million in maintenance costs annually as well as $6 million in infrastructure costs - which is a big win for us and them! Read their press release for more information.

Posted by Nitin Mangtani, Google Search Appliance Product Manager

We came across another interesting article published in New Idea Engineering in the series - "Enterprise Search: Mapping Security Requirements to Enterprise Search". In this article Mark talks about the importance of document level security and the two methods of implementing it. We completely agree with Mark on the importance of supporting document level security with enterprise search systems. Anything short of fine-grained access control is no security at all. The Google Search Appliance supports document level security across heterogeneous enterprise content stores.

While we agree with Mark on some of the benefits with using early-binding security filtering, there are certain limitations that make it impractical (if not impossible) to use for most deployments today. One of the main issues with early-binding is synchronization with the access control list (ACL) policies stored in content systems. ACL policies change frequently, and caching the ACL policies results in policies being out-of-sync with the source system. This can cause severe breaches in company security and allow sensitive IP to be leaked within the organization.

The second issue is the lack of implemented standards for introspecting the ACL policies. Without a standard way of reading policies from source systems, companies are faced with difficult implementations or are only able to provide secure results inside a homogeneous system. The new MOSS 2007 search system is a prime example of this, where security is only enforced on content that is stored in the Sharepoint system and not across other content systems, web servers, or databases.

At Google, we're working to establish a scalable, standards-driven way of early-binding security filtering. For that to work we need implemented standards within content systems (web servers, file servers, document management systems, portals, etc.) for introspecting and notifying changes in ACL policies. Until then we continue to support late-binding, document-level security filtering and delivering the highest quality, highly secure search results to tens of millions of users in companies worldwide every day.

Posted by Nitin Mangtani, Google Search Appliance Product Manager

In the last tech tip we talked about how the inmeta operator can be used to do sophisticated queries leveraging the metadata associated with your documents. What if your needs are more complex? You not only want to do queries based on specific meta tag values but also need to provide price range searches on your e-commerce site or date range searches inside your document management system. Luckily we added few interesting operators in the recent release of the Google Search Appliance and they will play nicely with the inmeta operator.

We added new operators for doing number (including price) and date range searches. For number range searches, just add two numbers, separated by two periods, with no spaces, into the search box along with your search terms. For date range searches, use the daterange operator. Let's take a look at some common examples and see these operators in action.

An e-commerce site sells electronics and apparel goods and wants to make it easier for it's customers to search products by keywords and also restrict the searches by price range and other numeric meta tags. For example to express a query that searches for rain jacket in the price range of $100 to $500 one would enter a query like:

rain jacket inmeta:retailprice:$100..$500

You can also express a query that searches flat panel TV between 30 to 50 inches; one would enter a query like:

flat panel TV inmeta:size:30..50

In case of enterprise search, a search-user may be interested in the documents within an ECM system like Documentum or Livelink that provide information about "marketing plan" but restrict to only those documents that were published between Jan 1 2006 to Nov 27 2006. To express such a query one would simply enter a query like:

marketing plan inmeta:publishdate:daterange:2006-01-01..2006-11-27.

I have also seen e-commerce sites that use the Google Search Appliance to power their search, implement a simple search front-end that has a search box and a price slider along with it. Search-users enter the keyword in the search box and pick the appropriate price or number range using the UI widget. The search front-end in turn converts that request to the appropriate search syntax described in the above examples. This way the search-user not only has the power to express complex searches but she also doesn't need to familiarize herself with the additional syntax.

These range-based operators are more examples of how you can provide the power and precision of Google search with the flexibility and customization that your business requires.

Posted by James Wang, Google Mini Team

Here they are, the first 3 Google Enterprise Search Superstars. This award recognizes companies, and the individuals involved, with innovative enterprise search implementations.

Titans of industry? Men among men? Juggernauts of their respective fields? You be the judge. We hope you enjoy their stories and glean a few things you can do to make your users, whether employees or customers, happier and more effective in finding what they are looking for.

Looking to get ideas about how to create search functionality that can recommend experts within your company about a topic? Learn more about this in Danny Perri's "Expert Search" implementation.

Do you have an international audience and want to get some ideas on how to improve your search and service? Read and hear how Chris Hall improved his site.

Would you like to learn more about turning your support site into a more self service portal and increasing the efficiency of support staff? Read and hear more about this from Razi Mohiuddin's story of improving the customer service experience.

If you own a Google Mini or Google Search Appliance, then here's your chance at Search Superstardom. Come share your story with us so we can share it with the world.

Posted by Nitin Mangtani, Product Manager, Google Search Appliance

There was talk in the Google Search Appliance group this week about the new inmeta query operator; I thought it's time to introduce this new feature to a wider audience.

In a recent release of the Google Search Appliance we added the inmeta query operator allowing search-users to easily create more advanced queries based on meta tag values. The appliance has had this capability for a long time using the requiredfields and partialfields parameters as part of the search API protocol. The inmeta operator allows search users to issue partialfields and requiredfields type searches directly from the search box (in the q= parameter).

The syntax is pretty simple:

inmeta:{meta_tag}
inmeta:{meta_tag}~{meta_tag_value}
inmeta:{meta_tag}={meta_tag_value}

The first query syntax shows how to issue a requiredfields search, which will restrict the results to any containing the meta tag specified. The second will execute a partialfields search with a value, matching any results that have that meta tag with a value matching some or all of the value specified in the query. The third is how to issue a requiredfields search matching the exact value specified in {meta_tag_value}.

For example, if you had content source with all documents having meta tag author and each document having a different value for author meta tag such as john, rajesh, mike, etc. A search-user may be interested in the documents that provide information about "Q3 Revenue" but restrict to only those documents that were authored by John, as John the CFO of the organization. To express such a query she would simply enter a query like:

Q3 revenue inmeta:author=john

Now, if you didn't know that the data was well formatted, and some might have John's full name (John Smith), and some might have his email address ([email protected]) then you would want to use the following syntax:

Q3 revenue inmeta:author~john

As you see from the above examples, it is very easy to express your queries and perform advanced, sophisticated searches across structured, semi-structured, and unstructured information. We welcome the new inmeta operator to the search town!

Posted by Rodrigo Vaca, Enterprise Team

Bom dia! A couple months ago we promised to enable more and more customers around the world to benefit from our enterprise search technologies.

Today we’re delivering another piece of that promise – and a big piece for that matter! We just launched Google Enterprise and announced immediate availability of our enterprise search products in Brazil. It was great to see the interest from customers and the press community alike.

For this launch we partnered with MUDE, BearingPoint, B2Bis, Added and Datacraft – great companies with lots of knowledge of the local market and customers. We’re very excited to have them on board helping customers with their enterprise search needs.

Now, if only the Google Search Appliance could help me find an excuse to make it to Rio around Carnival time… :)

Rodrigo Vaca

Posted by Kevin Smith, Partner Program Manager

Need to extend the reach of your Google Search Appliance to even more systems? Want professional services for your Google enterprise products? Just curious about what our Google Enterprise Professional partners are up to?

Look no further. We're happy to announce the launch of our partner webinar series, with demos, updates, and other information from a variety of our technology and consulting partners. You can find the schedule plus register for individual webinars by pointing your browser to:
www.google.com/enterprise/gsa/live_demos.html

Posted by David Bercovich, Product Marketing Manager

British Airways, the UK's largest international airline, has deployed two Google Search Appliances to help its 48,000 employees find information inside the company. With employees traveling all over the world and working all hours of the day, it is essential for BA to provide always on access to information on their internal network with Google.

And the employees like it. Accoring to Alan Huish BA's employee self-service programme manager, employee self-service satisfaction has risen from 60% to 78% since Google was deployed, and efficiency has improved because information is more readily available. With Google, BA has upgraded search to first class!