See only what you need to with Community Streams

We introduced Community Streams recently so you can easily view all your community activity in one easily accessible location. Following beta user feedback we’ve now added in some configuration settings so you decide what you see and how you see it.

You can now configure the following:

  • Types of Posts (Actions, Notes, Widget updates)
  • Time Period (1 day, 3 days, 1 week)
  • Communities

community stream config

For a reminder on how to get the Community Stream Click Here.

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We’re always interested in hearing from you with any comments or suggestions, feel free to get in touch.

 

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A new look for Widget Working View

We’ve given Widget Working View a face lift making it much easier for you to analyse, compare and  look for relationships and patterns. We’ve also added in a help link which takes you through to the Sabisu Wiki where you’ll find more information on how to use the analytics.

You’ll notice the analytics have been grouped according to the type of data you have selected so it’s easier to switch between discrete, continuous and project data.

wwv facelift

Obviously analytics can be a complex topic. If you’d like some guidance on how the analytics can be beneficial for you we can arrange a web conference with one of our tame and human-ready mathematicians – just get in touch. 

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We’re always interested in hearing from you with any comments or suggestions, feel free to get in touch.

 

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Sabisu in a PDF?

For some time now Sabisu has allowed users to save a Page or Widget into a Word document, or to export certain widgets to Excel. However, a popular User Group request was to export to PDF – so we’re pleased to deliver you exactly that.

Most users will always share Widgets and Pages with the platform as the interactive visualisations, inline analytics and collaboration are the cornerstones of the Sabisu experience. However, we know that sometimes you just need to send a PDF.

Simply navigate to the Page tab menu and select Print. You can then either export to Word or PDF.

PDF EXPORT

Don’t forget you can now embed Sabisu Widgets into intranet pages, blogs, SharePoint, digital signage…anywhere that takes HTML.

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We’re always interested in hearing from you with any comments or suggestions, feel free to get in touch.

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Sabisu Notes just got better

Sabisu Notes is an integral part of Sabisu where users collaborate, Add actions, share insights and now upload files too.

The uploaded file can be viewed by anyone within the Community – they’ll be able to download the file too. You can upload a file as supporting documentation for any Note that has been made.

upload files to notes

We’ve also updated the Sabisu Search functionality so that now you can now search for Notes across the platform. Clicking these Notes will take you to the most relevant page that Sabisu can find, even if the Widget is on multiple pages.

search notes

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We’re always interested in hearing from you with any comments or suggestions, feel free to get in touch.

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2017 Q2 Sabisu User Group – Agenda sneak peak

Following the success of our January User Group we’re been looking forward to the next one on May 11th and we’re excited to be able to share with you a sneak peak of the agenda.

If you can’t make it in person, we’d be delighted if you could join via web conferencing.

Agenda

09:00 – 09:30 Coffee, Cake and Chat

09:30 – 09:50  Introductions & Review

09:50 – 10:20  Forthcoming Features

10:20 – 10:45  Case Study : A presentation by CropEnergies AG

10:45 – 11:00  Interlude (more coffee, cake and chat)

11:00 – 11:25 Case Study: A presentation by SABIC UK

11:25 – 11:35 Actions on Mobile Devices

11:35 – 12:00 Q&A and customer suggestions 

Why should you get involved?

  • Get insight into how other customers get value out of Sabisu
  • First hand look at new and upcoming platform features
  • Provide valuable feedback on how you use Sabisu
  • Drive platform development to suit your needs
  • Get to know the Sabisu team

How do you get involved?

Simply email laura.ticehurst@sabisu.co or lynsey.nicholson@sabisu.co and we’ll send you an invitation.

When and Where?

11th May, 2017  9am -12pm

The Wilton Centre, Wilton, TS10 4RF.

Or via web conference.

Contact Us

We’re always interested in hearing from you with any comments or suggestions, feel free to get in touch.

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Introducing the Sabisu Handover Log

We’ll shortly be making the Handover Log available to all users in Sabisu.

The Handover Log will provide you with a one stop for any and all handovers; shift handovers, project teams, or anywhere one user/group needs to pick up where another left off.

You can create a Handover Log to take notes in a meeting and assign actions to users. The log can then be used as a working document to monitor progress.

handover log

For example, a Shift Handover Log is common in the process industries to give updates to the next shift on duty and handover any outstanding actions or concerns. This is a great use-case.

Sometimes projects will work back-to-back, with two people working the same role. The Handover Log ensures that the handover is complete and high quality without the need for a face to face meeting, or where that might be difficult.

You can add in current Actions or create new ones and in the next few days we’ll add file attachments too.

handover log 2

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We’re always interested in hearing from you with any comments or suggestions, feel free to get in touch.

 

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Machine Learning in Sabisu – Finding Patterns in Data

Machine learning allows users to leverage the inherent information contained within large datasets. This is not the top level information that is the raw data itself, but rather the secondary information that can be extracted through the elucidation of hidden patterns.

There are two forms of machine learning; supervised and unsupervised.

Supervised learning requires a labelled dataset, where different classes of behaviour are identified beforehand. This data is then fed into the machine learning algorithms, allowing them to learn the differentiating factors between these classes. Once this is done, a model is produced which can now be used to classify brand new data, predicting what class it belongs to from the original set. This classification process is used for tasks such as handwriting recognition, where a system will learn what the different letters look like using huge labelled datasets that contain different writing styles. The system can then “read” handwritten documents it has never seen before, identifying letters with incredible accuracy. This is how many countries sort their post, using handwriting recognition systems to read postcodes and route the letters to the correct regions.

However, in many cases labelled datasets aren’t available. Industrial process plants contain a large amount of data, often in the form of time series. These time series encapsulate the state of the plant at a very fine granularity but for a continuous process it is rarely straightforward to interrogate this data. Using unsupervised machine learning techniques it is possible to automatically separate different modes of operation by analysing the time series. An example of this is shown in figure 1, where the top panels show process data, and the bottom panels show how unsupervised machine learning has segregated this data into different operational modes.

Feature Detection

Figure 1A. Unsupervised learning identifies the different modes of behaviour by identifying patterns in the data. This can be used to identify similar behaviour in the future, or search the historical data for similar occurrences.

FeatureDetectionZoom

Figure 1B. Zooming in on individual features we can see the boundaries between the different behaviour as the colours change in the lower panel.

Processing in the Cloud

Machine learning is all about Big Data, and efficiently extracting value from this data. It is therefore natural to build machine learning solutions in the cloud, which provides seamless scaling of processing power to meet the demands of the data. Sabisu uses a variety of cloud technologies such as Amazon’s Elastic Map Reduce, Spark, and the Spark-ML libraries to ensure rapid processing of even the largest datasets. Data noise is always a concern in any time-series processing application. Sabisu has developed a set of custom aggregators in Python and Scala to ensure the best results from real-world data.

Simplifying Machine Learning

You don’t have to be an expert to use Sabisu’s machine learning solutions. On the contrary, the finer implementation details are abstracted from users to allow you to concentrate on the thing that really matters; the results!

Sabisu will handle all of the pre-processing and calibration required to make the most of this advanced technology, meaning all you have to do is select the data you want to analyse.

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We’re always interested in hearing from you with any comments or suggestions, feel free to get in touch.

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Dynamically update your widgets

New updates to the Sabisu Pipeline mean you’re now able to query Widget data from a Pipeline Data component. This means that you can now have a Pipeline that can be dynamically updated via another Widget on a Page, e.g., from a user-selected list.

Why is this useful?

This makes Pipeline generated Widgets as flexible as any traditionally built Widget. It means end-users with no programming knowledge can link Widgets together.

You could use this to, say, compare data over a period of time and in different instances so you can analyse the data to spot anomalies and patterns.

query a widget with pipeline

How do I do it?

To get set up you could get in touch and we’ll provide you a list Widget ready to go, so all you need to do is set up the pipeline:

create a query with pipeline

Or you could build your own Widget in the Sabisu Builder, then set up your acquisition within the Sabisu Pipeline to use it:

using builder

Contact Us

We’re always interested in hearing from you with any comments or suggestions, feel free to get in touch.

 

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Share Sabisu everywhere

You can now embed Sabisu Widgets into any web page.

This makes it easy to embed Sabisu into intranet pages, blogs, SharePoint, digital signage…anywhere that takes HTML.

The embedded widget will update with data as if it was in the Sabisu platform. Any user that needs to analyse the data or see it in contact can simply click the Sabisu logo to be taken into the platform proper.

To start embedding your Sabisu Widgets simply navigate to the widget tab menu and hit “Get Shareable Link”

shareable link

We have embedded a Sabisu widget into the blog post below. If you login to your Sabisu account you’ll see the data.

We’ve set Widgets free but they’re still super-secure; only users with appropriate access can see them. If you have a Sabisu account and you’re logged in to Sabisu, the Widget will automatically load, however if you don’t have an account or you’re not logged in you will be asked to sign in.

If you don’t have a Sabisu account….get in touch!

 

Contact Us

We’re always interested in hearing from you with any comments or suggestions, feel free to get in touch.

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Problem? Highlight & huddle with Sabisu Events

Sabisu now allows you to highlight a chart area and create an event, instantly notifying everyone in the Community that there’s something they need to know about.

As soon as you create the Event, it’ll be visible on the chart, the Widget Working View Notes, Community Notes and the Community Stream.

The Event could be anything; a sudden spike in the furnace pressure for example, or costs rising due to an unforeseen circumstance. If you find an Event needs more investigation you can assign an Action to the relevant person directly on the Notes stream.

Events

Rather than just a new type of Note, Events represent a new class of metadata capture for Sabisu which allows our machine learning algorithms to recognise repeating Events and inform you one has occurred or is about to occur. It will also analyse data using to be able to advise you when an event is likely to happen again. Watch this space.

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We’re always interested in hearing from you with any comments or suggestions, feel free to get in touch.

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