Betsy Ricotta

Betsy Ricotta

Navigating the Future: Entrinsik’s Unified Approach to Customer Support

At Entrinsik, enhancing your experience remains our utmost priority. In this spirit, we’re excited to share a significant stride in our journey – the formation of a Unified Support Team. This initiative is led by Robin Lamb, our Vice President of Client Services.

The formation of this unified support team demonstrates our continuous efforts to optimize support operations. Integrating the prowess of our experts from both Informer and Enrole, we’ve fostered a collaborative team dedicated to promptly and efficiently addressing your needs. Robin’s vision and leadership have been instrumental in catalyzing this significant transformation.

Our customer support team is routinely awarded top marks by third party reviewers, including three consecutive “Best in Customer Support” awards from BARC. The unified support team is the next step in Robin’s commitment to customer satisfaction, by seamlessly integrating the technical expertise of our Informer and Enrole specialists. We’ve built a team that not only understands your needs but also delivers timely, efficient solutions.

We believe this team is a significant stride towards realizing our commitment to your satisfaction and towards setting a new benchmark in customer support. We look forward to sharing more as we continue to evolve and innovate, keeping your needs and satisfaction at the center of our efforts. At Entrinsik, we’re not just about providing solutions; we’re about creating success stories together.

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Enrole Release 8.2.2

Enrole Release 8.2.2 is here, focusing on resolving reported bugs to enhance the stability and reliability of our platform. While no major features are introduced, this release tackles various issues that may have affected performance and functionality. Our dedicated team has fine-tuned the codebase, addressing bugs in user authentication, data synchronization, and UI inconsistencies. These fixes significantly improve overall performance, providing a seamless user experience. We extend our gratitude to users who reported bugs and provided valuable feedback. Upgrade to Enrole 8.2.2 by following our documentation or contacting our support team. We appreciate your continued support and look forward to serving you with more updates in the future. Stay tuned!

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Essential Steps for Finding the Perfect Software Solution

In today's digital age, software has become an indispensable tool for businesses and individuals alike. Whether you're looking for project management software, accounting tools, or creative applications, finding the right software solution can significantly enhance your productivity and efficiency. However, with the abundance of options available, it's crucial to approach the search process systematically. In this blog, we'll explore five essential steps to follow when searching for new software, ensuring you make an informed decision that meets your specific needs.

Identify Your Requirements:

Before embarking on your software search, take the time to clearly define your requirements and objectives. Identify the problems or challenges you're trying to solve, the specific features you need, and the goals you aim to achieve. Engage with key stakeholders and users to gather input and ensure that everyone's needs are considered. Creating a comprehensive list of requirements will serve as a roadmap and help you narrow down the options that align with your specific criteria.

Research and Compare Options:

With your list of requirements in hand, it's time to research and compare various software options available in the market. Utilize search engines, review websites, and software directories to identify potential solutions. Pay attention to factors such as functionality, user experience, scalability, and compatibility with your existing systems. Compile a shortlist of software products that best meet your requirements, and thoroughly review their websites, feature lists, and customer testimonials to gain deeper insights into their capabilities and limitations.

Read Reviews and Seek Recommendations:

While vendor websites can provide valuable information, it's equally important to seek external opinions and insights. Read reviews from reputable sources and software communities to gain a more objective understanding of each solution's strengths and weaknesses. Look for case studies and success stories from businesses or individuals in similar industries or with similar requirements. Additionally, reach out to colleagues, industry peers, or online forums for recommendations based on their firsthand experiences. This research phase will help you uncover valuable insights and ensure you make an informed decision.

Request Demos and Trials:

To truly gauge a software's suitability for your needs, request demos or trials from the shortlisted vendors. Demos provide an opportunity to interact with the software firsthand and see if it aligns with your workflow and user experience expectations. During the demo, ask questions, explore different features, and assess the software's ease of use. Similarly, trials allow you to test the software in your own environment, evaluate its performance, and determine its compatibility with your existing systems. Take advantage of these opportunities to gather feedback from end-users and ensure the software meets your requirements before making a purchase decision.

Consider Support, Security, and Scalability:

When evaluating software solutions, it's vital to consider factors beyond the core features. Assess the vendor's customer support offerings, including availability, response time, and the level of support provided. Determine whether they offer training materials, documentation, or user communities to assist with onboarding and troubleshooting. Additionally, prioritize security features and protocols to safeguard your data and protect against potential cyber threats. Lastly, consider the software's scalability to accommodate your future growth and evolving needs. Ensure that the solution can scale alongside your business and adapt to changing circumstances.

The process of finding the right software solution requires careful planning, research, and evaluation. By following these five essential steps, you'll be well-equipped to make an informed decision. Investing time and effort in the search process will lead to finding the perfect software solution that enhances your productivity, efficiency, and ultimately, contributes to your success.

 

Learn more about Enrole, an off-the-shelf registration management software at www.entrinsik.com/enrole

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Advanced Data Management & Analytics with Informer Cloud

Assessable Data

Welcome to a new era of data management, with fully hosted Informer, an advanced cloud-based data analytics platform. Benefit from a secure, scalable, and supremely flexible solution to access and evaluate all your business intelligence in one place. Whether you’re sharing your insights with customers and coworkers across the globe or building an automated data processing pipeline, Informer is always easy to use with a reactive UI and an intuitive REST API to support you.

  • Unified Data Integration: Consolidate disparate data sources with ease.
  • Real-time Data Analytics: Generate instant insights using real-time analytics and point-in-time data combined.
  • Scalability and Performance: Deliver exceptional performance, irrespective of data volumes.
  • Security: Protect your data with industry-leading security measures.
  • Customization and Flexibility: Tailor analytics and reporting to suit your specific needs.
  • Automation and Workflow: Automate data processing and improve efficiency.
  • Global Dashboard and Visualization Hosting: Serve rich and dynamic visuals to your customers and coworkers, no matter where they are.
  • Expertly Managed: Informer is managed in the cloud by the same people who develop it and know it best.

Informer Cloud Capabilities

Unified Data Integration

Informer Cloud empowers you to merge various data sources into one unified platform. Whether you need to bring together Snowflake, MSSQL, PostgreSQL, or even Pick-based systems like UniVerse and UniData, Informer can handle it. See all your data, all at once, and combine them to drastically improve the effectiveness of your decision-making.

Real-time Data Analytics

Harness the power of real-time data analytics. Informer Cloud provides dynamic data visualization tools, including Dashboards and charts, to help you monitor and interpret data as it is generated. Utilize this speed to stay ahead of emerging trends and make informed, data-driven decisions instantly. If you need to maintain point-in-time data for auditing or retrospective analysis, Informer has you covered as well. All of Informer’s advanced analytics tools can be used on Snapshots, spreadsheets or even prior exports. Informer’s global reach and vast capacity puts all of your data, past and present, at your fingertips.

Scalability and Performance

Informer Cloud is designed with scalability and performance in mind. Our Kubernetes-based architecture is constantly monitoring the cluster and ensuring a fantastic customer experience. We scale with you. Entire Informer instances are brought online rapidly to deal with periods of heavy load, and thanks to our stateless request-handling system, you’ll never notice when you’re suddenly talking to a completely new instance.

Security

With Informer Cloud, your data is protected by robust security measures. Our platform uses advanced encryption techniques both at rest and in flight, role-based access control, and is compliant to the highest standards of SOC2 criteria. We are constantly scanning for exploitable vulnerabilities and our SLA guarantees an industry-leading response to breaches and exploitations.

Customization and Flexibility

We don’t believe in “no” when it comes to your ability to get the most out of your data. Informer is extendable by nature, and that opens exciting possibilities for customizing it to fit your needs. Our Professional Services and DevOps teams have unfettered access to the codebase and are ready to implement your vision, seamlessly, into your cloud deployment. New authentication schemes, new database support, and customized UI elements are just a sample of what our team can do to make Informer your bespoke business intelligence platform.

Automation and Workflows

At the heart of Informer is a powerful and flexible data processing engine supported by an incredibly capable REST API. It is a cinch to integrate Informer into your existing workflows because our API is simple, self-documenting, and uses industry-standard formats like JSON and CSV to ingest, transform, and export data. Combine that capability with automated Jobs run by the system itself and there is almost no automated data processing pipeline that you can’t implement with Informer at its core.

Global Dashboard and Visualization Hosting

With Informer Cloud, your beautifully crafted Visuals and Dashboards can be embedded anywhere. No more fiddling with firewall exceptions or brittle VPN setups. You can embed your content in iframes, share links, and even embed static images with as few as three clicks. Of course, security is always our priority. You’ll be able to restrict access to your data based on an IP address or authentication token so you remain in control of who sees your data and where from.

Expertly Managed

At Entrinsik, our DevOps team also participates in Informer development. That means that they have incredible insight into how to manage, support, and deploy the application. Even more importantly, they provide intimate feedback about the SaaS experience to the rest of the development team to constantly improve the product and answer the needs of our cloud customers.

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Jobs For Supporting Data Analysis

Informer 5 Job Feature

Wouldn’t it be nice if you could email one filtered data view to a coworker and a different filtered view to another, save a data view to your file system, or even FTP it? And, do this all on a schedule! Well, Informer 5 Jobs enables you to do just that.

An Informer Job is a task or collection of tasks to be executed against data in your system. These tasks can be automated using a recurrence schedule, or simply saved in the system to be manually triggered when needed. The three main components of creating a Job are:

  • Identifying the data that the Job is going to be using
  • Selecting the actions that the Job will be executing based off the data
  • and, scheduling the Job

Jobs are tightly governed, and the individual or Team that creates a Job owns that particular Job and only certain roles are allowed to manage those Jobs.

Setting Up The Data

After you define the data to use from one or more Informer Dataset(s) or Ad hoc Queries, select whether you want the data to refresh for your data analysis whenever the Job is run.

For example, you can bring in the Dataset that contains all your organization’s sales across the country and then filter the Dataset per geographical region, resulting in four data components – Northern Sales, Southern Sales, Eastern Sales, and Western Sales. See Figure 1.

Setting Up The Actions

Define the set of tasks you would like executed against the data. For example, perhaps you would like to send an email to the Director of Sales – Northern Division with Visuals from the filtered Dataset Northern Sales, and send similar emails to the South, East, and West Directors of Sales. And, then store the filtered data components to the file system to perform data analysis. This can all be accomplished within the same Job. See Figure 2.

There are four options for Actions on a job and custom Actions specific to your organization can be easily introduced via a plugin:

  • Send an email – Use a rich email editor to send an email using content sourced from the Data components of the Job. You can also add file attachments to the email. For example: a new HTML file, text file, zip file, a file from the file system, or the Data components of the Job in a certain file format.
  • Send an email burst – Use a rich email editor to send emails to different individuals using specific content per email sourced from the Data components of the Job. You can also attach files to burst emails.
  • Send to file system – Save files to the file system of your Informer instance. Choose the files to send. For example: an HTML file, text file, zip file, upload files, or send from the Data components of the Job.
  • Send to FTP – Establish and send files via an FTP connection. Choose the files to send. For example: an HTML file, text file, zip file, upload files, or send from the Data components of the Job.

All the Actions above can be selected to ‘Run on a Condition’, where the Action is only run if there is a configurable threshold number of records in the data components.

Setting Up The Schedule

A Job can be run on a defined schedule or manually at any time. See Figure 3.

Informer provides tremendous flexibility in setting the interval of the schedule:

  • Minutes – You can designate a job to run every X minutes, starting at a designated date and time. For example: Run every 5 minutes.
  • Hourly – You can designate a job to run every X hours, starting at a designated date and time. For example: Run every 6 hours.
  • Daily – You can designate a job to run either every X day at a designated time or to run every weekday at a designated time. For example: Run every third day.
  • Weekly – You can designate a job to run on specific days of the week at a designated time. For example: Run every Monday, Wednesday, and Friday.
  • Monthly – You can designate a job to run on a specific date of a specific month or to run on the first/second/third/fourth occurrence of a given day of the week every X months. For example: Run on the third Wednesday of every second month.
  • Yearly – You can designate a job to run once a year on a specific date of a specific month or to run on the first/second/third/fourth occurrence of a given day of the week for a specific month.
  • Custom – You can also specify a cron expression for very granular recurrence schedules that are not covered above.

Jobs List Page & History of Jobs

All Jobs are listed on the Jobs List Page where you can see a snapshot of the Job by status. Details show the Owner, the Schedule for the Job, last run time, the next run time, status of the Job, when it was created, when it was last modified, and more. The History page lists all the recent fire times of the Job, who ran the Job, the duration of the Job, and the result of the Job, i.e., success, failed, or warning. See Figure 4.

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Data Visualization with Discover

Informer Discover Makes Visualizing Data Easy

With Discover, Informer 5 does a lot of the thinking for you by automatically serving-up interesting business intelligence Visuals based on the Filters and type of Fields you select. This is a huge timesaver!

In Discover, you simply click on the filter icon to identify the criteria you want to use to visualize and explore data on a macro level in your Dataset. See Figure 1.

You can also apply data filters to your individual charts within a multi-chart view without affecting the other visuals. Just select a field you want to analyze without being concerned with how you want to present it. Then quickly change the charts and other information.

Sort & Group Data Instantly

Discover groups all your Dataset column fields by data type (i.e., text, date, Boolean). This enables you to make quick selections and see resulting data visualization displays based on the type of field you choose. By selecting Boolean fields (Yes/No-type information) the resulting visual quickly shows you how many of the characteristic you have, or don’t have. See Figure 2.

Date fields generate trend analysis charts. Location fields generate geographic maps (e.g. heat maps, Google Maps, state maps, county maps, etc.). You can also combine multiple selection fields to aggregate information into a singular chart, for example: revenue, gender, age, location. The Leaderboard visual provides a ranking based on values associated with what you are aggregating.

Visualize Data in Multiple Ways

Visual options vary depending on the type of data visualization you are configuring:

  • A pop-up list enables you to change the chart type. You can also change the title and description for the Visual.
  • For graphical Visuals such as pie or column charts, you can change the chart type, Y-axis value, primary and secondary grouping value, and maximum number of items to show.
  • If the selected Field is a date, you have the option to change the Interval (Year, Month, Day, Month of Year, etc.).
  • For Leaderboards, you can change the Field to display the aggregate value used for ranking See Figure 3.
  • Pivot tables allow you to change the Fields used for rows and columns, as well as the aggregate value used in the body of the table.

Filtering on Areas of Interest

Filters are a very powerful data analytics productivity tool in Informer. They enable you to easily narrow down your data to focus on your area of interest. There are two types of data Filters within Informer – Dataset Filters and Visuals Filters.

Visual Filters – In addition to the overall Dataset Filters, Visuals have their own Visual Filters that apply to a specific Visual. Discover displays all the selectable fields within its Visual Card view, as shown in Figure 3. When you select different combinations of these fields, you will see how easy and fun it is for you to uncover new insights into your data from all the Visuals served up. To narrow down your Dataset even further, simply continue to add more Filters. See Figure 4. You can merge multiple filters together or save a specific filter. You can also save the filters for your Visual in your Datasets.

Dataset Filters – Enable you to narrow the scope of Visuals so you can quickly glean business intelligence insight into your area of interest without needing to configure charts or graphs. For example, if you select a location based field, Discover will automatically present heat maps highlighting the data behind the location field, (e.g., a Visual of Total Student Enrollment across the United States). By selecting a combination of fields, you automatically see Visuals like Trend Charts, Leaderboards, Averages, Totals, and Statistics.

Discover Reports

There are two types of Reports used in Discover: Dashboard Reports and Comparison Board. After choosing the Dataset you would like to visualize and selecting a field to group your data, you will be presented with several different Visual options (Date Fields, Text Fields, and Numeric Fields).

  • Date Fields display Visuals such as trend charts, pivot tables or statistics. (See Figure 5).
  • Text Fields – For text fields such as country, state, or city, using maps and possible leaderboards or other similar charts would best complement your data visualization. To generate new Visuals from text fields, choose your desired values underneath the fields indicated by green quotation mark icons. (See Figure 6).
  • Numeric Fields – Create statistics, total boxes, leaderboards, and similar charts. (See Figure 7).
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Datasets: The Foundation For Successful Data Analytics

Create a Single Source of Truth

Data exists everywhere throughout your organization: in databases, on shared network servers, in the cloud, on countless desktops. Data also exists in various formats: as records in multiple types of databases, as structured text files, as proprietary spreadsheet documents, as streams from REST calls to a 3rd party API. Informer enables you to discover business intelligence from all these disparate silos but first you’ll want to get your data into the form of an Informer Dataset.

A Dataset is the elementary building block for Informer content to perform data analytics. A Dataset is a set of indexed Records and a Record is a collection of Fields. A Field can be a simple value such as a number or text, an object, or an array of objects.

Creating Datasets From Structured Files

You can create Datasets from existing documents by simply dragging a document with a supported file format from your desktop onto any location in Informer. See Figure 1. Informer will create a new Dataset from the file content. It’s that easy! Currently supported formats include Comma Separated Values (.csv), JSON (.json), and Excel documents (.xls, .xlsx). As with supported Datasource types, Informer will support more file format types over time.

Informer Workspace

While dragging in an individual static document file to create a Dataset is ideal for doing quick one-off analytics, creating an Informer Workspace provides more flexible and governed access to the set of data. A Workspace is a collection of associated source documents which Informer treats as a virtual database. It enables you to create mapping associations and other standard Datasource functions just like a traditional database. Workspaces are ideal for importing multiple files for business intelligence.

Dataset Designer

The Dataset Designer makes it easy for you to create a Dataset visually by using Mappings. You do not need to be an expert! It is especially useful for those who don’t know the Datasource’s query language and/or are not intimately familiar with the schema and structure of the underlying Datasource.

After choosing a Datasource and Mapping for your query within Dataset Designer, just select Fields and Criteria — the two primary components of a Query:

  • Fields define what details you want to see about the records you’ll be retrieving from a Datasource. Datasets can be customized to show only certain Fields by adding the desired Fields within your Query. Add as many Fields as you want. You can also add Fields from other Mappings. See Figure 2.
  • Criteria enables you to pare down which records are retrieved.

For example, let’s say you have an Orders table with historical details of orders including product details, shipping details, billing details, etc. The Fields you choose for the Dataset determine what you ultimately view from the selected records. If you want a Dataset to include only those orders containing a specific product, you would add that restriction within your Criteria.

Add more Mappings if would like to. You can add a link or an SQL link:

  • Add Link – Pair up Fields between Mappings. Add as many new Fields as you’d like.
  • Add SQL Link – Join tables to create a joint Mapping.

Add Criteria To the Query

Criteria defines which records are retrieved from your Dataset for your data analytics. You can include Criteria within a Dataset or Ad-hoc Query Report. You can also choose whether you want a Criteria to be based off a Field or Value. See Figure 3.

  • You can select the condition for the Criteria, for example “exactly matches”. Select either a Value, Field, or Input to compare the first part of the condition.

Flows

For more in-depth business intelligence, Flows enables you to augment your Dataset records with additional data, metadata, or logic as your Dataset records are indexed. You can easily derive new values from your existing data as well as cleanse bad data from your Datasource. Within the Dataset, you have the options to:

  • Create new Fields that perform certain functions against one or more selected Fields from the Dataset or Fields from a different Dataset. See Figure 4.
  • Configure the Fields that you’ve added by adjusting data types, replacing Field values, removing duplicates, and splitting Fields with multiple values. See Figure 5.
  • Include advanced power scripting which adds more advanced programming capabilities to the Flow step process to further derive new values or cleanse existing data.
  • Remove Fields that you’ve added.

Refreshing Your Dataset

There may be occasions where you want to periodically refresh one of your Datasets. Refreshing enables you to update the data in your Dataset with current data from your Datasource, manually or automatically via an Informer Job. See Figure 6.

An Informer Job is a task or collection of tasks to be executed using data in your system. These tasks can be automated using a recurrence schedule, or simply saved in the system to be manually triggered when needed.

Alternatively, you can easily append data to a Dataset without replacing all your current data. See Figure 7.

Native SQL

If you have an existing query statement, or if you are comfortable with authoring one and simply don’t want or need to use the Dataset Designer… Native SQL is for you! Just choose a Dataset Name and a Datasource against which to execute your query. Click Query and begin typing. You’ll notice the rich editor offers autocomplete and color coding for both SQL syntax and schema as shown in Figure 8.

Upon execution of your query, Informer provides progress updates and forwards you to the Dataset Explorer page containing your query result, once the results are available. You now have a Dataset that’s ready for data analytics!

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Extensibility with Plugins and APIs

An Open Architecture

By employing an open architecture based on end-to-end 100% JavaScript, AngularJS and plugins, Informer 5 is designed to be highly adaptable, flexible and scalable. Informer makes it easy to integrate with other modern JavaScript libraries and to write, test, share, and deploy plugin code. This architecture offers many benefits to you for data analysis.

For example, you can bring in:

  • Unique customizations
  • Input forms
  • Authentication schemes
  • Datasources
  • Datasets
  • Flow steps
  • Mappings
  • Visuals
  • and other functionality into the system.

Plugins

Plugins enable the system to be safely customized (by customers, system integrator partners, and our own services team) to meet customer requirements without the need for a new software release. These customizations can also be easily shared between users and organizations via Github or the NPM Central Repository.

The possibilities with plugins are really limitless. New functionality or customized features can be easily added to the system to support your data analysis. You can have a plugin that automatically provides links between tables in your Datasource, or a customized formatted output, for example: invoice, or a new visual type, or a new logo or color scheme, etc.

Interacting with APIs

Informer 5 offers a rich, flexible, and easy-to-understand REST API for external programs to interact with. We decided early on in the development process that almost all of the interaction between our UI and our server would be done via this API – thereby ensuring it is robust and usable for customers who want to tightly integrate Informer 5 with their other applications for improved data analysis.

Overview of REST

APIs which use standard http(s) interactions as their method of interaction are referred to as RESTful. You can use a REST client of your choice. Interaction with Informer 5’s API is accomplished by issuing carefully crafted, PUT, POST, GET, and DELETE HTTP commands to specific URLs on the Informer server, and then interpreting the response the server gives. In this way, you can interact directly with Informer 5’s server outside of the UI.

All REST requests are authenticated and authorized by the Informer server. Informer supports three authentication methods:

  • Session – Uses a session cookie set after a successful login and carried with each REST request.
  • Token – A query parameter attached to a request URL that allows access to a set of routes relevant to accessing the asset for which the token was created.
  • Basic – HTTP Basic authentication method where username and password are communicated using the HTTP Authentication Header.
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Data Governance and Security

Security and Governance by Design

Data governance and security lie at the heart of Informer 5 by incorporating organizational governance policies at the data level, content level, and functional level security. Informer strikes a balance between enabling self-service analysis and protecting your organization’s sensitive business intelligence information. And, it provides transparency and traceability of data, while maintaining data integrity and data quality.

With data governance and security functionality designed into the system from inception, Informer answers questions like:

  • ‘How can I trust the data?’
  • ‘How can I ensure that only authorized persons can see the data, or parts of it?’
  • ‘How can I have traceability of key business decisions?’
  • ‘How do I keep my data from getting unwieldy and uncontrollable?’

Informer 5 utilizes a Teams security model to specifically support real world business operations and security needs. A Team within Informer is defined as a group of Users that comprise a logical business unit within an organization. The Roles within a Team are determined by one’s business role. Your organization’s logical groups and security rights for your employees map easily into Informer’s Teams and Roles.

Teams provide identity access management via an intuitive model whereby you can secure your data and access to it. You can easily determine why a specific User or Team has the rights to perform a specific action or access specific content. As a result, it is easy to audit usage of the system and content and provide users with a single source of truth for content.

The Teams model ensures that:

  • Access to sensitive data is secured
  • The data used for reporting has not been doctored
  • Shared data is current and accurate
  • Users interact with and access the data based on determined security settings
  • Only those with determined access rights can alter the query behind the data.

Privilege Access Management with Users

Users are assigned certain access rights within Informer based on their role within your organization and business intelligence needs determined by their system administrators. In addition to the typical username, password, and email, a user must be defined as either a Normal User or a Super User. See Figure 1.

  • Normal Users have no special privileges outside of Team-based Roles and Security.
  • Super Users have full access rights to the entire system, superseding any Team-based Role assignment. A Super User can view all content within the system, including all fields within a given Datasource, and can modify any Datasource, Dataset, Report, or Job. Only a Super User can define another User as a Super User.

Identity Access Management with Teams

While Users are the individuals with access to Informer, typical business intelligence activities within an organization are completed by groups of individuals comprising a department or logical business unit within a department. See Figure 2. By nature, different groups have different access rights to business data. And, since members of a group have different functional roles, their access rights within the group differ as well. For example, some members of a department create data content for an organization, while others simply use the data to build business insights.

Every Team has a Team Landing Page for identity access management. From the Team Page, you can view and manage the list of all Users and their Roles, the list of Datasets, Reports, and Datasources owned by the Team, and the list of Datasets, Reports, and Datasources shared to the Team.

Defining an individual’s role within the Team is an important aspect of identity access management and adding a Member to a Team. Informer 5 provides comprehensive pre-defined role types for Team members with sensible access rights. See Table 1. These role types map easily to your organization’s security permissions for your employees.

Role Name Rights
Member View anything Owned by the Team
Designer All Member rights
Create content from Datasets available to the Team.
Upload spreadsheets into new Datasets.
Create Reports from Datasources available to the Team.
Data Wizard All Designer rights
Create Workspaces
Create Datasets from Datasources available to the Team.
Edit Team-owned Datasets.
Publisher All Data Wizard rights
Share Team-owned Datasets and Reports to other Teams.
Admin All Publisher rights
Manage members
Add a Datasource to the Team
Share a Team-owned Datasource to other Teams

Table 1: Team Roles

As Teams model logical business units within an organization, Users can be Members of more than one Team. Their role within a specific Team is determined by their business role with respect to that Team. For example, the Manager of the Graduate Students Division of the Registrar’s office in a University may be the Admin for the Graduate Student Team as well as a Data Wizard for the larger Registrar’s Team. In the scenario where an individual has different roles in different Teams with access to the same content, the highest role permissions will prevail. For example, in the case above, the Manager would have Admin privileges for any content that is available to both the Graduate Student Team and the Registrar’s Team.

As with Users, you can also source Teams from a third-party repository using Informer’s Plugin Architecture. For example, Teams can be retrieved for use in Informer by referencing Divisions within your organizational chart and applying those Users and Teams to Informer together with the appropriate Roles. As a User is introduced into Informer, they are assigned to a default Team determined by the Informer system administrators. For example, connect Informer via LDAP and assign to an umbrella Team for the organization named All Employees.

Ownership of Content for Strong Data Governance

Ownership of content (Datasource, Dataset, Report, and Job) is a powerful concept in Informer 5. It implies quality and confidence in the content. All content in the system has a single Owner. Ownership can be by an individual User or a Team, with the typical scenario being a User owning the content while creating and iterating on it, and eventually passing on Ownership to the Team once finalized. When content is owned by a Team, it represents a credible single source of truth providing for Data Governance.

Ownership is an important part of privilege access management as it implies privileges on the content and determines who can modify an entity. As a result, the content quality is preserved and once shared with others, holds credibility. If the Owner is a User, then the User is considered an Admin for the content with all functional privileges – create, edit, copy, delete. If the Owner is a Team, then the Role within the Team determines the privileges on the content. See Table 1: Team Roles for role definitions and privileges.

Best Practices Data Governance Example for Creating & Ownership of a Dataset

Bob is a member of the Human Resources Team with a Data Wizard role. He creates a Company Attrition Rate Dataset by pulling in appropriate data and creating Data Flows. He is the Owner of the Dataset and thus considered the Administrator of the Dataset. This is now his personal workspace to iterate on the creation of the Dataset.

After he is satisfied with the Dataset, he changes Ownership from himself to the Human Resources Team. The Team can then iterate on the Dataset in a collaborative fashion. Once the Dataset is finalized, the Publisher role within the Human Resources Team can then decide to which other Teams the Dataset should be shared. The Dataset now holds credibility as it is owned and shared by the Human Resources Team within the organization. This example of privilege access management applies to all content – Datasets, Reports, and Datasources – and provides Data Governance.

Sharing Content Confidently

Organizations rely on departments to share content between each other reliably and confidently. Sharing content while tracking edits and editors enables Teams to create a library of curated content and provides for Data Governance. With Informer, providing content access to members outside of your Team is tightly controlled and monitored.

In Informer 5, Datasets and Reports are either shared across Teams in full (though read-only), regardless of a User’s role within the shared Team, or not shared at all. Users with the appropriate Role within the owning Team have edit capability.

Datasource Sharing

Role Name Rights
No Access Default – Datasource does not appear
Limited Access Only the Query Designer may be used to create Datasets.
No Restricted Fields
Full Access Datasource can be queried without any restrictions
Custom Access Only the Query Designer may be used to create Datasets.
Selected Mapping Sets only (choose whether to allow Restricted Fields)

Table 2: Datasource Access Roles

Dataset & Report Sharing

Sharing a Dataset provides read-only access to the selected Teams while the Dataset Owner retains editing access to the Dataset. Privilege access management determines when sharing a Dataset, the Sharing Team must select the level of access being given to the selected Team (No Access, Full Access, or Custom Access) See Figure 3.

Custom Access gives only a Filtered view of the Dataset to the selected Team filtered out of the view. This is a way to also achieve row level security.

Sharing a Dataset does not include sharing associated Reports — those must be shared explicitly. Even though sharing a Report implies access to underlying Datasets for the purposes of the Report, Users can only filter. The underlying Datasets are not available as source for other content and will not display as an available Dataset outside the scope of the shared Report.

Datasource & Report Sharing

Sharing a Datasource provides Teams with query access to the Datasource as specified on an individual Team basis:

  • Limited Access
  • Full Access
  • Custom Access
  • or No Access

Selecting a level of access for the Shared Team involves choosing an access level for their:

  • Data Wizard
  • Publisher
  • and Administrator

The available levels of privileged access management and their respective rights are detailed in Table 2.

Role Rights
No Access Default – Datasource does not appear
Limited Access Only the Query Designer may be used to create Datasets.
No Restricted Fields
Full Access Datasource can be queried without any restrictions
Custom Access Only the Query Designer may be used to create Datasets.
Selected Mapping Sets only (choose whether to allow Restricted Fields)

Table 2: Datasource Access Roles providing privilege access management

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