New Intune Release – Desktop and Mobile Device Management and Security

As part of the name change to ‘Microsoft Intune’ a new look and feel has been released this week.  Contact the Atidan team at for information on how to manage and secure all of your devices.

New Intune standalone features that will be released as part of this service update include:

  • Enhanced user interface for Intune administration console
  • Ability to restrict access to Exchange on-premises email based upon device enrollment
  • Bulk enrollment of devices using a single service account
  • Lockdown of Supervised iOS devices and devices using Samsung KNOX with Kiosk mode
  • Targeting of policies and apps by device groups
  • Ability to report on and allow or block a specific set of applications
  • Enforcement of application install or uninstall
  • Deployment of certificates, email, VPN and WiFi profiles
  • Ability to push free store apps to iOS devices
  • More convenient access to internal corporate resources using per-app VPN configurations for iOS devices
  • Remote pin reset for Windows Phone 8.1 devices
  • Multi-factor authentication at enrollment for Windows 8.1 and Windows Phone 8.1 devices
  • Ability to restrict administrator access to a specific set of user and device groups
  • Updated Company Portal apps to support customizable terms and conditions

Intune Mobile App Management - AtidanMicrosoft Intune - Atidan

Mobile Device Management (MDM)

With the increasing volume and diversity of corporate and personal devices being used in organizations today, a growing challenge for IT departments is keeping corporate information secure. Intune helps minimize complexity by offering mobile device management through the cloud with integrated data protection and compliance capabilities.

  • Provide a self-service Company Portal for users to enroll their own devices and install corporate applications across the most popular mobile platforms
  • Deploy certificates, WiFi, VPN, and email profiles automatically once a device is enrolled, enabling users to access corporate resources with the appropriate security configurations
  • Deliver comprehensive settings management for mobile devices, enabling the execution of remote actions such as passcode reset, device lock, data encryption, and full wipe to protect corporate data on lost or stolen devices
  • Protect corporate data by restricting access to Exchange email when a user tries to access resources on an unenrolled or non-compliant device based upon policies set by the administrator
  • Simplify enrollment of corporate devices with bulk enrollment using Apple Configurator or a single service account, enabling IT administrators to set policies and deploy applications on a large scale
  • Enable the enforcement of more strict “lock down” policies for Supervised iOS devices, Android devices using Kiosk Mode, and Windows Phone devices using Assigned Access
Mobile Application Management (MAM)

Employees are demanding access to corporate applications, data, and resources from their mobile devices. Intune addresses this challenge by building manageability and data protection directly into the Office mobile apps your employees are most familiar with. Intune also provides the flexibility to extend these capabilities to existing line-of-business apps and to enable secure viewing of content using the Managed Browser, PDF Viewer, AV Player, and Image Viewer apps.

  • Enable your workforce to securely access corporate information using the Office mobile apps they know and love while preventing leakage of your company’s data by restricting actions such as copy/cut/paste/save in your managed app ecosystem
  • Apply the same management policies to your existing line-of-business (LOB) applications using the Intune app wrapper, without requiring code changes in those LOB apps
  • Allow users to securely view content on devices within your managed app ecosystem using the Managed Browser, PDF Viewer, AV Player, and Image Viewer apps for Intune
  • Allow administrators and device users to protect corporate information through selective wipe of managed apps and related data when a device is unenrolled, no longer compliant, lost, stolen, or retired from use
  • Enable administrators to push required apps automatically during enrollment and allow users to easily install corporate apps from the self-service Company Portal
  • Provide the ability to deny specific applications or URL addresses from being accessed on mobile devices
PC Management

As the number of device types allowed in corporate environments grows, management becomes more challenging. Intune provides a comprehensive management solution through a single administrative console that allows you to manage across a variety of devices, including PCs and laptops.

  • Integrate your existing System Center 2012 Configuration Manager infrastructure with Intune, further enhancing your ability to manage PCs, Macs, and Unix/Linux servers, as well as mobile devices from a single management console, while building on existing investments and skills
  • Provide real-time protection against malware threats on managed computers, keep malware definitions up-to date, and automatically scan computers to help protect against malware infections and other potentially unwanted software
  • Collect information about hardware configurations and software installed on managed computers, allowing you to generate reports, organize groups of computers, and more effectively target software deployments
  • Simplify administration by deploying software and configuring Windows Firewall settings on computers based upon policies defined by the administrator

Internet Explorer IE Site Discovery Toolkit – Prioritize Application Compatibility Testing

Upgrading to the latest version of Windows typically requires Enterprises to do full line of business app compatibility testing with the latest version of Internet Explorer. What makes this a difficult task for most Enterprises is that they often do not know which of their catalog of internal line of business applications are critical and used by their employees. Often times this leads IT Pros to test all of their internal apps, even ones that may not be used, which can be a costly and time consuming process. In addition to testing, it can be difficult to mitigate compatibility issues without knowing more about how the application is built.

Download page:

The Enterprise Site Discovery Toolkit is a way for an IT Pro to better understand how their users are browsing with Internet Explorer 11. This toolkit enables collecting information from Internet Explorer 11 about all sites that are visited by their users to build an inventory of sites used in the Enterprise. This information will help IT Pros prioritize which applications they should focus their app compatibility testing with Internet Explorer. This tooklit also provides additional information on how the site is designed and used by Internet Explorer and that information can then be used to populate the Enterprise Mode site list, mitigating compatibility issues of critical sites. By default, Internet Explorer will not collect this data; you have to enable collection if you want to use it.

Once enabled, data will collected on all sites visited by Internet Explorer 11 except while browsing in an InPrivate browsing session. Additionally, this data collection is silent and there is no end user notification that information is being collected. You must make sure that you ask the necessary consent and comply with all applicable local laws and regulatory requirements before enabling this in your deployment of Internet Explorer 11.

Fuzzy LookUp for Excel – Prelease Download – Identify Textually Similar Data

Microsoft Fuzzy Lookup Add-In for Excel

A challenging problem in data management is that the same entity may be represented in multiple ways throughout the dataset. For instance, customer “Andy Hill” might also be present as “Mr. Andrew Hill” or “Hill, Andrew R.”. Variations can result from merging independent data sources, spelling mistakes, inconsistent naming conventions and abbreviations, or records with additional/missing information.

Microsoft Fuzzy Lookup technology, developed by Microsoft Research, allows you to quickly identify data records which are textually similar. You can identify fuzzy duplicates within a single table or perform a fuzzy join between two different tables. The default configuration works well for a wide variety of data, but the matching may also be customized for specific domains.

Fuzzy Lookup for Excel Beta - Atidan


System Requirements

The add-in works on any Microsoft Windows operating system with Microsoft Excel 2010 or newer installed.

Installation Steps

Close any open instances of Excel. Uninstall any existing versions of Microsoft Fuzzy Lookup Add-in For Excel using the Windows control panel. Navigate to, then download and run Setup.exe to launch the installation wizard.

If Setup.exe is run with administrator privileges, it will be installed for all users on the machine. It will be installed only for the current user otherwise.

Once successfully installed, launch Excel and you should see a Fuzzy Lookup tab in the Excel Ribbon bar.

See Portfolio Sample section for an introduction on how to use the add-in.

Installation Folder

The add-in, documentation and samples will be installed to the folder:

If the installer is run without administrator privileges,

%LOCALAPPDATA%\Microsoft\Fuzzy Lookup Add-In For Excel\         %LOCALAPPDATA% is typically C:\Users\%USERNAME%\AppData\Local

If the installer is run as administrator on a 32-bit operating system,

%ProgramFiles%\Microsoft\Fuzzy Lookup Add-In For Excel\         %ProgramFiles% is typically C:\Program Files

If the installer is run as administrator on a 64-bit operating system,

%ProgramFiles(x86)%\Microsoft\Fuzzy Lookup Add-In For Excel\         %ProgramFiles(x86)% is typically C:\Program Files (x86)

Portfolio Sample

This section describes how to use the Fuzzy Lookup Add-In for Excel with the spreadsheet Portfolio.xlsx which is located in the installation folder.

Imagine you have a stock portfolio described by two columns Company and Shares and that you are interested in computing the average price/earnings (P/E) ratio of the companies in the portfolio. To do this, you need to join your portfolio table with another table containing P/E ratios. The spreadsheet contains a second tab called SP500 which contains company data imported from the stock screener at the website. Looking at the data, one can see that an exact join on the Company columns of the two tables would fail as the string representations of the companies differ (e.g., “AMAZON COM INC STK” and “ Inc.”).

A fuzzy join of the two tables can be performed as follows:

  1. Turn the each data range into an Excel table by selecting a region and pressing CTRL-L. You can assign a name to the table clicking on it and selecting the Design tab in the Excel ribbon.
  2. Open the Fuzzy Lookup pane by clicking on the Fuzzy Lookup button in the Fuzzy Lookup tab of the Excel ribbon.
  3. Pick the left and right tables from the drop down menus. Matching rows from the right table will be returned for each row in the left table.
  4. Select the columns to match on. If the two tables share one or more column names in common, a default join will already have been added. If you wish to match on different columns, first delete the existing join by pressing the “X” button on the join row in the Match Columns table. To create a new column binding, select one or more columns from each table (multiple columns may be selected by holding down SHIFT or CTRL and click on the column names). Next, press the button in between the two lists of columns to add a row to the Match Columns table.
  5. Select one or more output columns to be output for each match.
  6. Select the maximum number of matches to be returned for each left row.
  7. Set the similarity threshold. All matches returned must have a similarity greater than or equal to this value.
  8. Move the current cell selected in the Excel spreadsheet to an empty cell which has empty space to the right and below it. The Fuzzy Lookup matches will be output starting at this cell.
  9. Press the “Go” button to perform the match.

One should see the results as indicated in the screenshot above. Notice that each returned match includes a similarity score indicating how close the two records are. 1.0 means an exact match while lower scores indicate less similarity.

Note that Fuzzy Lookup can also be used to identify matches in a single table by setting the left and right tables to be the same.

Advanced Concepts

Fuzzy Lookup technology is based upon a very simple, yet flexible measure of similarity between two records.

Jaccard similarity

Fuzzy Lookup uses Jaccard similarity, which is defined as the size of the set intersection divided by the size of the set union for two sets of objects. For example, the sets {a, b, c} and {a, c, d} have a Jaccard similarity of 2/4 = 0.5 because the intersection is {a, c} and the union is {a, b, c, d}. The more that the two sets have in common, the closer the Jaccard similarity will be to 1.0.

Weighted Jaccard similarity and tokenization of records

With Fuzzy Lookup, you can assign weights to each item in a set and define the weighted Jaccard similarity as the total weight of the intersection divided by the total weight of the union. For the weighted sets {(a, 2), (b, 5), (c, 3)}, {(a, 2), (c, 3), (d, 7)}, the weighted Jaccard similariyt is (2 + 3)/(2 + 3 + 5 +7) = 5/17 = .294.

Because Jaccard similarity is defined over sets, Fuzzy Lookup must first convert data records to sets before it calculates the Jaccard similarity. Fuzzy Lookup converts the data to sets using a Tokenizer. For example, the record {“Jesper Aaberg”, “4567 Main Street”} might be tokenized into the set, {“ Jesper”, “Aaberg”, “4567”, “Main”, “Street”}. The default tokenizer is for English text, but one may change the LocaleId property in Configure=>Global Settings to specify tokenizers for other languages.

Token weighting

Because not all tokens are of equal importance, Fuzzy Lookup assigns weights to tokens. Tokens are assigned high weights if they occur infrequently in a sample of records and low weights if they occur frequently. For example, frequent words such as “Corporation” might be given lower weight, while less frequent words such as “Abracadabra” might be given a higher weight. One may override the default token weights by supplying their own table of token weights.


Transformations greatly increase the power of Jaccard similarity by allowing tokens to be converted from one string to another. For instance, one might know that the name “Bob” can be converted to “Robert”; that “USA” is the same as “United States”; or that “Missispi” is a misspelling of “Mississippi”. There are many classes of such transformations that Fuzzy Lookup handles automatically such as spelling mistakes (using Edit Transformations described below), string prefixes, and string merge/split operations. You can also specify a table containing your own custom transformations.

Jaccard similarity under transformations

The Jaccard similarity under transformations is the maximum Jaccard similarity between any two transformations of each set. Given a set of transformation rules, all possible transformations of the set are considered. For example, for the sets {a, b, c} and {a, c, d} and the transformation rules {b=>d, d=>e}, the Jaccard similarity is computed as follows: Variations of {a, b, c}: {a, b, c}, {a, d, c} Variations of {a, c, d}: {a, c, d}, {a, c, e} Maximum Jaccard similarity between all pairs: J({a, b, c}, {a, c, d}) = 2/4 = 0.5 J({a, b, c}, {a, c, e}) = 2/4 = 0.5 J({a, d, c}, {a, c, d}) = 3/3 = 1.0 J({a, d, c}, {a, c, e}) = 2/4 = 0.5 The maximum is 1.0. Note: Weghted Jaccard similiary under transformations is simply the maximum weighted Jaccard similarity across all pairs of transformed sets.

Edit distance

Edit distance is the total number of character insertions, deletions, or substitutions that it takes to convert one string to another. For example, the edit distance between “misissipi” and “mississippi” is 2 because two character insertions are required. One of the transformation providers that’s included with Fuzzy Lookup is the EditTransformationProvider, which generates specific transformations for each input record and creates a transformation from the token to all words in its dictionary that are within a given edit distance. The normalized edit distance is the edit distance divided by the length of the input string. In the previous example, the normalized edit distance is 2/9 = .222.

Technical resources

For more technical details on Fuzzy Lookup, see the following resources:

Microsoft Research Data Cleaning Project

Transformation-based Framework for Record Matching

Efficient Exact Set-Similarity Joins

Help and Support

The Fuzzy Lookup Add-in for Excel is pre-release software and no support is officially provided by Microsoft.

A forum for questions about the add-in is available here:

Questions and comments may also be sent to

This document is provided “as-is”.  Information and views expressed in this document, including URL and other Internet Web site references, may change without notice. Some examples depicted herein are provided for illustration only and are fictitious.  No real association or connection is intended or should be inferred.  This document does not provide you with any legal rights to any intellectual property in any Microsoft product. You may copy and use this document for your internal, reference purposes.

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