Category Archives: Google

What will happen in the information sector in 2017?

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As we look back at 2016, we can say that it has been an exciting and groundbreaking year that has changed how we handle information. Let’s look back at the major developments from 2016 and list key focus areas that will play an important role in 2017.

3 trends from 2016 that will lay basis for shaping the year 2017

Cloud

There has been a massive shift towards cloud, not only using the cloud for hosting services but building on top of cloud-based services. This has affected all IT projects, especially the Enterprise Search market when Google decided to discontinue GSA and replace it with a cloud based Springboard. More official information on Springboard is still to be published in writing, but reach out to us if you are keen on hearing about the latest developments.

There are clear reasons why search is moving towards the cloud. Some of the main ones being machine learning and the amount of data. We have an astonishing amount of information available, and the cloud is simply the best way to handle this overflow. Development in the cloud is faster, the cloud gives practically unlimited processing power and the latest developments available in the cloud are at an affordable price.

Machine learning

One area that has taken huge steps forward has been machine learning. It is nowadays being used in everyday applications. Google wrote a very informative blog post about how they use Cloud machine learning in various scenarios. But Google is not alone in this space – today, everyone is doing machine learning. A very welcome development was the formation of Partnership on AI by Amazon, Google, Facebook, IBM and Microsoft.

We have seen how machine learning helps us in many areas. One good example is health care and IBM Watson managing to find a rare type of leukemia in 10 minutes. This type of expert assistance is becoming more common. While we know that it is still a long path to come before AI becomes smarter than human beings, we are taking leaps forward and this can be seen by DeepMind beating a human at the complex board game Go.

Internet of Things

Another important area is IoT. In 2016 most IoT projects have, in addition to consumer solutions, touched industry, creating a smart city, energy utilization or connected cars. Companies have realized that they nowadays can track any physical object to the benefits of being able to serve machines before they break, streamline or build better services or even create completely new business based on data knowledge. On the consumer side, we’ve in 2016 seen how IoT has become mainstream with unfortunate effect of poorly secured devices being used for massive attacks.

 

3 predictions for key developments happening in 2017

As we move towards the year 2017, we see that these trends from 2016 have positive effects on how information will be handled. We will have even more data and even more effective ways to use it. Here are three predictions for how we will see the information space evolve in 2017.

Insight engine

The collaboration with computers are changing. For decades, we have been giving tasks to computers and waited for their answer. This is slowly changing so that we start to collaborate with computers and even expect computers to take the initiative. The developments behind this is in machine learning and human language understanding. We no longer only index information and search it with free text. Nowadays, we can build a computer understanding information. This information includes everything from IoT data points to human created documents and data from other AI systems. This enables building an insight engine that can help us formulate the right question or even giving us insight based on information to a question we never ask. This will revolutionize how we handle our information how we interact with our user interfaces.

We will see virtual private assistants that users will be happy to use and train so that they can help us to use information like never before in our daily live. Google Now, in its current form, is merely the first step of something like this, being active towards bringing information to the user.

Search-driven analytics

The way we use and interact with data is changing. With collected information about pretty much anything, we have almost any information right at our fingertips and need effective ways to learn from this – in real time. In 2017, we will see a shift away from classic BI systems towards search-driven evolutions of this. We already have Kibana Dashboards with TimeLion and ThoughtSpot but these are only the first examples of how search is revolutionizing how we interact with data. Advanced analytics available for anyone within the organization, to get answers and predictions directly in graphs and diagrams, is what 2017 insights will be all about.

Conversational UIs

We have seen the rise of Chatbots in 2016. In 2017, this trend will also take on how we interact with enterprise systems. A smart conversational user interface builds on top of the same foundations as an enterprise search platform. It is highly personalized, contextually smart and builds its answers from information in various systems and information in many forms.

Imagine discussing future business focus areas with a machine that challenges us in our ideas and backs everything with data based facts. Imagine your enterprise search responding to your search with a question asking you to detail what you actually are achieving.

 

What are your thoughts on the future developement?

How do you see the 2017 change the way we interact with our information? Comment or reach out in other ways to discuss this further and have a Happy Year 2017!

 

Written by: Ivar Ekman

Migration from Google Search Appliance (GSA) in 4 easy steps

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Google Search Appliance is being phased out and in 2018, renewals will end. As an existing client, you can buy one-year license renewals throughout 2017. However, if fancying a change, here’s 4 simple steps for switching to Apache Solr or Elasticsearch.

1. Choose your hosting solution or servers

Wikimedia_Foundation_Servers-8055_14 

Whereas Google Search Appliance comes ready to plug in, Apache Solr and Elasticsearch need to be deployed and hosted on servers. You can choose to host Solr or Elasticsearch on your own infrastructure or in the cloud. Both platforms are highly scalable and can be massively distributed.

  • Own infrastructure

Servers and hardware requirements are highly dependent on the number of documents, documents types, search use cases and number of users. Memory, CPUs, disk and network are the main parameters to consider.

Elasticsearch hardware recommendations: https://www.elastic.co/guide/en/elasticsearch/guide/current/hardware.html

Apache Solr performance: https://wiki.apache.org/solr/SolrPerformanceProblems

Both Elasticsearch and Solr requires running java. For SolrCloud, you will also need to install Zookeeper.

  • In the cloud

You can also choose to run Solr or Elasticsearch on a cloud platform.

Elastic official cloud platform: https://www.elastic.co/cloud

2. Define your schema and mapping

In Apache Solr and Elasticsearch, fields can be indexed and processed differently according on type, language, use case … A field and its type can be defined in Elasticsearch using the mapping API or in Apache Solr with the schema.xml

Elasticsearch mapping API: https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping.html

Apache Solr schema: https://wiki.apache.org/solr/SchemaXml

3. Tune your connectors

the-cable-guy

Do you need to change all connectors?

The answer is no. Connectors sending GSA feeds can be kept, just refactor the output to match the Elasticsearch or Solr indexing syntax.

However, if you use GSA to crawl websites, you will need either to reconsider crawling as the method to get your data or to use an external webcrawler (like Norconex) Contrary to GSA, Apache Solr and Elasticsearch do not come with a webcrawler.

Elasticsearch Indexing API: https://www.elastic.co/guide/en/elasticsearch/reference/current/docs-index_.html

4. Rewrite your queries and fetch new output

All common query functions such as filtering, sorting and dynamic navigation are standard in both Apache Solr and Elasticsearch. However, query parameters and output (XML or JSON) are different, which means queries and front-end need adaption to your new search engine.

If you are using Jellyfish by Findwise, queries and output will roughly be the same.

Elasticsearch response body: https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-body.html

Apache Solr response: https://cwiki.apache.org/confluence/display/solr/Response+Writers

Google Search Appliance features equivalence

GSA feature Elasticsearch Apache Solr
Web crawling X X
Language Bundles Languages Language Analysis
Synonyms Synonyms Synonyms
Stopwords Stopwords Stopwords
Result Biasing Controlling relevance Query elevation
Suggestions Search-suggesters Suggester
Dynamic navigation Aggregations Faceting
Document preview X X
User result X X
Expert search X X
Keymatch X X
Related Queries X X
Secure search Shield Solr Security
Search reports Logstash+Kibana X
Mirroring/Distributed Scale Elastic Solr Cloud
System alert Watcher X
Email update/Alert Watcher X

X = not available outside of the box

New look for the GSA-powered file share search at Implement Consulting Group

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The file share search on Implement Consulting Group’s intranet is driven by a Google Search Appliance (GSA). Recently, with help from Findwise, the search interface was given a new look, that integrates more seamlessly with the overall design of the intranet.

GSA comes with a default search interface similar to the Google.com search. The interface is easy to customize from GSA’s administrative interface, however, some features are simply not customizable by clicking around. Therefore, GSA supports the editing of an XSLT file for customizing the search. GSA returns the search results in XML format, and by processing this file with XSLT we can customise how the search results look and behave.

Custom CSS and JavaScript was used for integrating GSA’s search functionalities in the look and feel of the intranet. Implement’s new intranet is based on thoughtfarmer.com and the design was delivered by 1508.dk.

— And here is the search results page with a new look:

icg-gsa-screenshot-findwise

The new look of the search results page on Implement Consulting Group’s Google Search Appliance powered search

Impressions of GSA 7.0

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Google released Google Search Appliance, GSA 7.0, in early October. Magnus Ebbesson and I joined the Google hosted pre sales conference in Zürich where we had some of the new functionality presented and what the future will bring to the platform. Google is really putting an effort into their platform, and it gets stronger for each release. Personally I tend to like hardware and security updates the most but I have to say that some of the new features are impressive and have great potential. I have had the opportunity to try them out for a while now.

In late November we held a breakfast seminar at the office in Gothenburg where we talked about GSA in general with a focus on GSA 7.0 and the new features. My impression is that the translate functionality is very attractive for larger enterprises, while the previews brings a big wow-factor in general. The possibility of configuring ACLs for several domains is great too, many larger enterprises tend to have several domains. The entity extraction is of course interesting and can be very useful; a processing framework would enhance this even further however.

It is also nice to see that Google is improving the hardware. The robustness is a really strong argument for selecting GSA.

It’s impressive to see how many languages the GSA can handle and how quickly it performs the translation. The user will be required to handle basic knowledge of the foreign language since the query is not translated. However it is reasonably common to have a corporate language witch most of the employees handle.

The preview functionality is a very welcome feature. The fact that it can highlight pages within a document is really nice. I have played around to use it through our Jellyfish API with some extent of success. Below are two examples of usage with the preview functionality.

GSA 7.0 Preview

GSA 7 Preview - Details

A few thoughts

At the conference we attended in Zürich, Google mentioned what they are aiming to improve the built in template in the GSA. The standard template is nice, and makes setting up a decent graphical interface possible for almost no cost.

My experience is however that companies want to do the frontend integrated with their own systems. Also, we tend to use search for more purposes than the standard usage. Search driven intranets, where you build intranet sites based on search results, is an example where the search is used in a different manner.

A concept that we have introduced at Findwise is search as a service. It means that the search engine is a stand-alone product that has APIs that makes it easy to send data to it and extract data from it. We have created our own APIs around the GSA to make this possible. An easy way to extract data based on filtering of data is essential.

What I would like to see in the GSA is easier integration with performing search, such as a rest or soap service for easy integration of creating search clients. This would make it easier to integrate functionality, such as security, externally. Basically you tell the client who the current user is and then the client handles the rest. It would also increase maintainability in the sense of new and changing functionality does not require a new implementation for how to parse the xml response.

I would also like to see a bigger focus of documentation of how to use functionality, previews and translation, externally.

Final words

My feeling is that the GSA is getting stronger and I like the new features in GSA 7.0. Google have succeeded to announce that they are continuously aiming to improve their product and I am looking forward for future releases. I hope the GSA will take a step closer to the search as a service concept and the addition of a processing framework would enhance it even further. The future will tell.

Findability and the Google Experience

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In almost every findability project we work on, users ask us why finding information on their intranet is not as easy as finding information on Google. One of my team members told me he was once asked:

”If Google can search the whole internet in less than a second, how come you can’t search our internal information which is only a few million documents?”

I don’t remember his answer but I do remember what he said he would have wanted to answer:

”Google doesn’t have to handle rigorous security. We do. Google has got millions of servers all around the world. We have got one.”

The truth is, you get the search experience you deserve. Google delivers an excellent user experience to millions of users because they have thousands of employees working hard to achieve this. So do the other players in the search market. All the search engines are continuously working on improving the user experience for the users. It is possible to achieve good things without a huge budget. But I can guarantee you that just installing any of the search platforms on the market and then doing nothing will not result in a good experience for your users. So the question is; what is your company doing to achieve good findability, a good search experience?

Jeff Carr from Earley & Associates recently published a 2 part article about this desire to duplicate the Google experience, and why it won’t succeed. I recommend that you read it. Hopefully it will not only help you meet the questions and expectations from your users; it will also help you in how you can improve the search experience for them.

Enterprise Search and why we can’t just get Google.