Archive for data visualization

Coolest New Power BI Features Revealed!

Recently the Microsoft Business Applications Summit 2019 highlighted new Power BI features and these are the coolest features to note IMO:

1. New Power BI App Workspace Experience in Preview Power BI App Workspaces were introduced to enable collaboration amongst the data/business analysts within an organization. The new experience introduces numerous improvements to better enable a data-driven culture including:

•   Managing access using security groups, distribution lists, and Office 365 Groups
•   Not automatically creating an Office 365 group
•   API’s for Admins, as well as new tools for Power BI Admins to effectively manage workspaces

2. Printing Reports via Export to PDF
You can now easily print or email copies of reports by exporting all visible pages to PDF.

3. Bookmark Groups
Now you have a way to organize bookmarks into groups for easier navigation.

4. Python Integration in Preview
Now data scientists can use Python in addition to R within Power BI Desktop.

5. New Visual Header
More flexibility and formatting options have been added to the header section of each visual.

6. Tooltips for Table and Matrix Vizs
Report page tooltips are now available for the table and matrix visuals

7. Many to Many Relationships in Preview
You will now be able to join tables using a cardinality of “Many to Many” – prior to this feature, at least one of the columns involved in the relationship had to contain unique values.

And now I’ve saved the best for last!

8. Composite Models in Preview
With this feature, you’ll now be able to seamlessly combine data from one or more DirectQuery sources, and/or combine data from a mix of DirectQuery sources and imported data. For example, you can build a model that combines sales data from an enterprise data warehouse using DirectQuery, with data on sales targets that is in a departmental SQL Server database using DirectQuery, along with some data imported from a spreadsheet.

As you can see there are many new features to digest but it would be well worth your while to follow the links provided.

On a closing note, I’d like to give you a teaser for two new features coming up soon that will have a huge impact on self-service data prep and querying for big data:

  • Dataflows
  • Aggregates

Stay tuned!
Mario Di Giovanni, BASc, MBA, CBIP
Director, Business Analytics

More about Mario

 

Partnership Provides Powerful Member Engagement Analytics

(Washington, DC—August 13, 2018) Association Analytics, the leading data analytics software and services company for associations, and Higher Logic, the industry leader in cloud-based engagement platforms, have announced their formal partnership.

Sharing the goal of innovating associations through technology, this dynamic union originated on May 23, 2018. An unprecedented case study detailing the impact of this new integration was released at the ASAE Annual Conference, featuring the predictive membership engagement and revenue indications ASAE has captured.

Higher Logic’s Director of Partnerships, Bobby Kaighn, explained, “What may surprise association leaders is the potency of analytical trends when the Higher Logic community platform is integrated with Association Analytics’ Acumen data analytics platform. You can see the exact retention rate of members who engage in specific community activities, the relationship between community interactions and attendance at annual meetings, and the ratio of membership revenue to the frequency of online community participation.”

Associations dedicate their sources to storing information on everything from finances to event registrations, and most of these sources are continually upgrading their advanced reporting functions to include visual analytics. Now imagine if an association could lay these advanced data sets, like marketing campaign data (from one source), on top of member engagement statistics (from another source). This is where the synchronized connectivity of this partnership innovates the association industry.

Higher Logic’s data-driven approach helps organizations track and manage meaningful interactions along each stage of the member journey. Its expanded suite of engagement capabilities includes online communities and marketing automation, covering everything from the initial web visit to renewal and ongoing engagement.

Julie Sciullo, CEO of Association Analytics, said, “With Higher Logic as a standard Acumen platform integration, we’ve been able to quickly and easily import community data in real-time to interpret past and current data, bringing trends to light for strategic action plans.  The integration with Higher Logic empowers associations to overlay hundreds of data combinations to gauge performance and predict future outcomes.”

With the partnership between Association Analytics and Higher Logic already innovating associations, today’s announcement is shared in celebration of this ongoing and increasing benefit to the industry. For more, don’t miss the latest case study featuring ASAE’s actionable analytics on retention rates, the relationship between specific interactions and attendance at annual meetings, and the ratio of membership revenue to the frequency of online engagement.

Association Analytics (A2) is an industry leader in data analysis and management products, services, and training. We innovate associations by funneling your databases continuously into one powerful visual analytics dashboard for real-time, instant interpretation and decision-making power. The platform is called Acumen and it’s designed specifically for associations. This hassle-free, hosted analytics platform means you no longer need IT staff to run reports. Acumen is intuitive and easy-to-use with out-of-box visualizations & reports that encourage cross-staff adoption. The flexible design allows you to choose only the modules you need and includes seamless built-in integrations with your AMS, LMS, email, and finance platforms. Modules include Membership Engagement, Events, Community, Finance, Membership, Sales/Orders, Email Marketing/Automation, and the Executive Dashboard feature. It’s time you had a single source of truth with a 360 degree view for better, faster decisions, enhanced member experiences, improved staff efficiency, and increased revenue. Learn more at www.associationanalytics.com

Higher Logic is an industry leader in cloud-based engagement platforms. Our data-driven approach gives organizations an expanded suite of engagement capabilities, including online communities and marketing automation. From the initial web visit to renewal and ongoing engagement, we help you track and manage interactions along each stage of the digital customer experience. Organizations worldwide use Higher Logic to bring people all together, by giving their community a home where they can interact, share ideas, answer questions, and stay connected. Everything we do – the tools and features in our software, our services, partnerships, best practices – drives our ultimate goal of making your organization successful. Visit www.higherlogic.com.

Planes, Trains, Automobiles… and Meetings

Each Labor Day weekend, analysts discuss the impact of gasoline prices and other factors on travel driven by an extra day off and the symbolic end of summer. Some estimates indicate that a greater number of travelers by car saved a collective $1.4 billion this year, much of which was spent elsewhere during trips.map-clipart-travel-map
Deciding if and when to travel greater distances is a more complicated process since it often requires relatively expensive air travel with a commitment in advance. The price of airline tickets is significantly determined by the timing of purchase relative to travel. Analytics indicate that the optimal time to purchase tickets is generally between three and eight weeks prior to travel. The specific timing changes based on the time of year and also varies significantly by departure and arrival airports. It unfortunately does not require advanced analytics to observe that prices tend to rapidly increase beginning two weeks prior to travel.
Associations effectively create similar opportunities for customers through meetings and events. Associations spend considerable time and effort on planning and marketing activities based on a range of customer data including prior event participation, topical interests, individual engagement, meeting sessions, organization characteristics, continuing education requirements, and demographics. Registration patterns are closely monitored against prior year’s activity and current goals. Sometimes these patterns are not consistent with historical data. In some cases a trend of early registrants fails to continue and in other cases a late surge of registrants follows a period of marketing efforts.
Associations can supplement their AMS data with external sources to help explain such patterns. The U.S. Census Bureau makes very useful geographic data available including zip codes with latitude/longitude mapped to several other data points. The Census Bureau also offers an application programming interface to obtain detailed geographic data for specific addresses. This data can be used to calculate the distance between two points (it’s kind of a long story that involves the trigonometry I never thought I would use such as sine, cosine, and inverse tangent). Tableau data visualization software provides out-of-the-box geographic visualization capabilities based on data including zip code, area code, city, metropolitan/micropolitan statistical area, and even congressional district.
Various surveys and other analytics estimate that a common comfortable distance for car travel is around 200 miles.  Here is a map created using Tableau showing the population density by zip code within a 200 mile radius of Phoenix:
Phoenix
Here is a similar map based on the same color scale for Chicago:
Chicago
A far greater number of individuals are likely to consider driving to a meeting in Chicago than a meeting in Phoenix. It is important to note that this straight line distance is clearly a rough estimate and encountering a large body of water such as Lake Michigan would challenge even the most dedicated meeting attendee. Fortunately you can leverage more advanced data sources such as the Google Maps API to estimate driving distances.
This data provides associations with great analytics opportunities to drive meeting participation by aligning with customer travel decisions. For example, marketing campaigns can consider travel decision timing and target specific airport markets. Registration pricing deadlines for individual events can incorporate location analytics. Your association can also create opportunities for strong customer engagement through efforts to help groups of potential meeting attendees organize buses together or even carpool.
Deriving travel distance analytics from customer location data is an example of gaining value from data. This demonstrates why it is important to consider analytics when designing business processes throughout the organization and not just as part of analysis after the fact. Increased meeting attendance often contributes to other benefits including member retention, publication revenue, engagement, and membership recruitment.
Understanding the impact of customer travel scenarios is a great way to leverage association analytics to create the future and grow your number of happy conference attendees.
 

Association Analytics: Begin with the End in Mind

Often association leaders ask me, “Where is the best place for us to begin our data analytics initiative?”  I like this question and am reminded of Steven Covey’s expression that before we undertake a new initiative, we should “begin with the end in mind”.  When it comes to data analytics for associations, this means starting with your strategic plan.
One association’s strategic plan, for example, specified that they would grow meeting attendance by 10% in 3 years.  This was their largest source of revenue.
In the past the association made decisions by looking at historical trends and was unable to confidently estimate expected attendance, revenue, venue amenities needed, onsite staffing levels and more.  In fact, the more events they held, the greater the risk of an incorrect estimate.
Yet because of the strategic initiative to increase attendance, the first thing they tried was to increase the number of events and market them by email campaigns and direct mail.
The visualization below is a simple bar chart showing the number events by year. The higher the bar, the more events. The color shading of the bars indicate the number of registrants. The darker the green, the more registrants. We can quickly see 2010 had the most events, but not the most registrants.  In other words, although the association increased the number of events, this did not increase the number of attendees. In fact, holding more events actually caused a decrease in meeting profitability as a whole, since there were more expenses associated with fewer registrants.
events
By reducing the number of events by combining smaller, similar events to a larger meetings, the organization was able to dramatically exceed the target set by the board.  In other words, by holding fewer events, they had more participants.

What is the Cost of Not using Data?

When making business decisions it’s important to weigh the costs of:

  1. Bad decisions
  2. Decision delay
  3. Lost opportunities
  4. Damage to image/reputation

Often these costs are much greater than the costs associated with analyzing data. Taking a “decision tree” approach can be a logical way to evaluate where to start:

  • Are there areas in your strategic plan where data can answer questions, provide insight and direction?
  • Which areas do our customers care about? Will it make a difference to them – add more
    value, improve their experience – advance our mission?
  • Do we have the data – or can we get it?
  • Will we be able to take action on the results of the analysis?

 

How to Choose the Right Visualization for your Association

Choosing the right data visualization is as important as choosing the right outfit to wear to an important meeting. Although your alma mater’s sweatshirt is perfect for the ball game, a suit and tie is more appropriate when trying to convince your board to increase your budget. Similarly, you are going to catch some flack for showing up to the game in a suit and tie! Choosing the right visualization for your audience is similar to choosing the right outfit for the function.
Did you know that the human brain is able to process images three times faster than text? From our primitive beginning, we’ve depended on our brain’s ability to detect subtle patterns and interpret meaning. So, how do you choose the right visualization? Let’s take a look at some common types of visualization and when they should be used to effectively communicate the story your data is telling.

Tabular

table

  • Best used when exact quantities of numbers must be known.
  • Numbers are presented in rows and columns and may contain summary information, such as averages or totals.
  • This format is NOT favorable to finding trends and comparing sets of data because it is hard to analyze sets and numbers and the presentation is cumbersome with larger data sets. It is estimated that the visual working memory has a capacity of about seven items. This means that you can store up to 7 bits of information (like numbers) in your brain’s “RAM” simultaneously. If you build a table with financial information for each month of the year for different areas of your association, it becomes difficult to find outliers or even the most profitable month.
  • This kind of visualization is likely what many association staff are accustomed to (think of all those excel spreadsheets floating around your office) so you may need to use a tabular format in conjunction with one of the other types listed below to convey the information.
  • A variation of the tabular chart is a highlight table. A highlight table applies color to the cell based on its value. The use of color can make outliers stand out more.

 Line Charts

line chart

  • Best used when trying to visualize continuous data over time.
  • Line charts use a common scale and are ideal for showing trends in data over time.
  • Example: membership or registrant counts throughout the year compared to previous years.
  • Trend lines and goal lines can also be added to compare actual counts with certain benchmarks.

Bar Charts

bar chart

  • Best used when showing comparisons between categories.
  • The bars are proportional to the values they represent and can be shown either horizontally or vertically. One axis of the chart shows the specific categories being compared, and the other axis represents discrete values.
  • Example: Bar charts can be helpful when looking at certain segments of your customers, registrants or members.
  • Goal lines can also be added to compare the actual counts with your benchmarks.
  • A variation of the bar chart is the stacked bar chart. This incorporates the use of color to visually show how certain segments add up to the total. In the example above, it’s easy to see that while 2010 Conference attendance counts are higher, the number of Paid attendees actually decreased from the previous year.
  • Another variation of the bar chart is called a bullet chart. This chart allows you to take a single measure (for example, revenue) and compare it to another measure (for example, revenue goal). It also can display percentiles.

bullet chart

Pie Charts

pie chart

  • Best used to compare parts to the whole.
  • Pie charts make it easy for an audience to understand the relative importance of values.
  • Using this format for more than 5 sections is not recommended as it can become difficult to compare the results. Too many sections make interpretation difficult because the difference between the sections can become too narrow to effectively interpret.
  • Often, even when wanting to compare parts to the whole, a bar chart can be more effective.

In addition to difference chart types, the use of filters and sorting is important to increase the association staff person’s ability to explore the data in more detail.
The goal of any visualization should be to communicate the information in the most concise and impactful way by using the appropriate visualizations for your data.  Effective visualizations enable your audience to quickly understand the story in the data and speeds the ability for association staff to reach key insights.

Data Discovery – a “Bicycle for the Mind”

Steve Jobs said that computers are like a “bicycle for the mind” allowing us to go further faster with less effort.  Within the field of business intelligence, I believe data discovery should be the same, amplifying our intelligence and creativity, allowing us to see patterns and insights which we can use to create the future of our organizations.

Data Visualization is Key

A key feature of data discovery is the ability to present data visually in order to quickly convey the information to our brains.  The goal is to stimulate our minds and then to allow us to interact and have a direct “conversation” with the data.  We “ask” follow-on questions by clicking through and moving elements on the screen, “re-presenting” the data many ways.
We are inspired when we see data visually and notice how it changes based upon the questions we ask.  We can see the power as we interact with the data and the analysis process becomes a natural extension of the activity of thought, enabling us to drill down, drill up, filter, bring in more data sources, or create multiple visual interpretations.  Interactivity supports visual thinking.  We can work with the data visually at the speed of thought, rather than writing queries to the databases.  We can learn and reach insights faster.  When we interact with the data visually, we are participating in the data discovery process and data becomes our partner in gleaning the information that becomes business intelligence.

How Does your Association Make Decisions Today?

An MIT study shows that most organizations still rely on instinct, intuition, politics and tradition.  But according to Harvard Business Review, top performing organizations are 5x more likely to use data to make decisions.  If we know that decisions based on data tend to be better decisions, why don’t we use it all the time?  Research says that only 15-20% of organizations believe they have access to the data they need in order to make good decisions.  Why is this?
IVeniceMonet once heard it explained this way – imagine you are Monet and you are explaining to a friend how to create a painting of Venice at twilight – like this one.  You might say, start out with a church steeple on the left sort of a brownish color and surround it by a golden light, with deep blue in the sky.  Oh yes, and maybe add some little purple/violet touches in the water to the right.  Do you think your friend would create a painting that looks like this one?  Probably not.  And yet that is what is happening daily between business and IT.  Business tries to describe in words the data that they want to see.  And IT tries their best to represent in reports and dashboards what they heard the business say.
The way it typically works is you have a question and ask IT to create a query or report and then when they deliver it, usually you have another question, or want another piece of data or have it grouped a different way.  Traditionally this change request has been considered a BAD thing!  And then you have to wait for IT to revise it.  At least that’s what used to happen to me when I worked for an association.  This process doesn’t really work well for either the IT department or the business users in the association trying to make decisions.

Change the Ending

Association staff want access to their data!  They don’t know their questions until they start to see the data.  Data discovery enables them to have a conversation with the data directly.  Data discovery allows all of us to shift perspective quickly and change the way we look at a problem.  We can cycle through different views deliberately trying to get the insight to pop out!
This is how we learn to understand the story our data is telling.  And once we understand the story, we can change the ending.

How to Configure Dashboard Subscriptions and Alerts on Tableau Server

One of the valuable features of a business intelligence platform is the ability to subscribe to updates of your association dashboards. We like the way this is handled with Tableau Server, and created this short guide to explain how it works.  In this case, the Tableau Server and the SMTP server are on the same machine.  You will need additional configuration if the two servers are on different hardware.

1. Setup the SMTP server on your Tableau Server

  • From the Start menu, click Control Panel.
  • Double-click Add or Remove Programs.
  • From the left pane, click Turn Windows features on or off.
  • Select Features
  • Click Add Features
  • Install SMTP Server

2. Configure the SMTP Server

  • Type IIS in your start bar search, click Internet Information Services 6.0 Manager
  • Expand your local computer and you should see a SMTP Virtual Server
  • Right click on Virtual Server and select Properties
  • On General tab, select IP address of local machine (Google “what is my IP” if you can’t tell)
  • On Access tab, click Relay, add your IP to the Computer access list

ISS pic

 

3. Test SMTP Server

  • Create a text file containing the following:

                                       From: myname@mydomain.com

                                      To: myname@ mydomain.com

                                       Subject: testing

                                       This is the test message body.

  • Copy the text file in the server’s pickup folder (default is here:   C:inetpubmailrootPickup)
  • The file should disappear and the test email will be sent to email if the server is working

4. Configure Tableau Server to Enable Subscriptions

  • Open Tableau Server Configuration
  • Click on the Email Alerts/Subscriptions tab
  • Select Enable email subscriptions checkbox
  • Input the IP for your SMTP server in the SMTP Server field (or the name if you know it)
  • Port 25
  • No Username or Password required if you used the default SMTP setup
  • Create Send email from (eg dskisthegreatest@associationanalytics.com)…It does not need to be a functioning address
  • Under Tableau Server URL, put the url to your Tableau server (eg http://dashboards.abccorp.com)
  • Click OK, Type the password for a Tableau Administrator in the General Tab, Click OK again
  • Note you will need to Stop the Server by running the “Stop Tableau Server” icon for the configuration to apply and then restart using the “Start Tableau Server” icon to apply the changes

5. Test the Subscription

  • Logon to Tableau Server
  • Find the dashboard for which you want to subscribe
  • You should see a envelope icon in the top right hand corner
  • Click it, and set the subscription
  • You should start receiving emails containing the dashboard on the intervals defined in the subscription!

Envelop Tableau

The Value of Data Discovery for Associations

The Magic Quadrant

In February 2013, Gartner Inc. released an important report entitled Magic Quadrant for Business Intelligence and Analytics Platforms which details the current state of the business intelligence (BI) market and evaluates the strengths and weaknesses of several of the top vendors. It’s interesting to note that in this report, Gartner emphasized the emergence of data discovery into the “mainstream business intelligence and analytics architecture”, something we have been highlighting at DSK Solutions for years.
What is data discovery? Associations and nonprofits are sitting on large quantities of data and don’t always realize the value of this powerful asset. The old days of spray and pray are gone. Remember direct mailing blasts? How ineffective! Associations were shooting in the dark and wasting resources that could have been allocated to better serve members. Unfortunately, some associations still rely on this marketing approach, but there is a better way: segmented target marketing based on data.
All of your data – including CRM or AMS (customer data), general ledger and budget (financial data), and Google Analytics (Web data), can be pooled together to illuminate your member strategy. Think of each data source as a small flashlight that reveals a little bit of the path in front of you. When your data sources are pulled together, the path becomes much clearer. When analyzing your data with data discovery, it becomes possible to discover things you did not know before.

Necessary Steps

Clients frequently come to us seeking guidance on how to begin the task of leveraging their data to inform better decision making. Before you can embark on data discovery, you have to do two things:

  • Ask the right questions.  What is meaningful to your organization? What are you trying to find out about your members, prospects, products, services and profit?
  • Clean your data. If your data is filled with duplicates, inaccuracies, inconsistencies and other forms of noise, your analysis will be flawed. Remember: Garbage in, garbage out.  Quality data as an input allows for accurate analysis as an output, which results in the improved ability to make good decisions.

These two steps form the foundation of the data discovery process. Almost always, the answers you derive from your data will lead to more questions. It’s okay to ask why. In fact, you should be asking why! Start by asking questions like these:

  • How dependent is your association on dues revenue?
  • What is the price elasticity of membership (Full Rate v.s. Discounted Rate)?
  • Which members are at risk for not renewing?
  • How far (in miles) will registrants travel to attend a meeting?
  • Which products or services have the highest profit?

Then start asking “why”.  Remember the idea of the Ishikawa (or fishbone) diagram?  It’s an easy and useful way to begin thinking in terms of cause and effect – you ask “why” 5 times, until you arrive at the root cause of an effect.  Now with interactive data discovery you ask these questions directly by interacting with the data in a visual way!  At DSK we describe it as “having a conversation with your data”.  For example, a certification department of an association wanted to look at their pass/fail ratio for an exam.  Using data discovery, they discovered many more college-aged people were registering and doing poorly than in the past.  In the process of asking “why” the failure rate was increasing, they discovered an opportunity not only to publish a new study guide, but also they located an entire new source of prospective members and created a new membership type to serve the college market.
Data discovery is an iterative process where you ask questions of your data in an interactive way. Drilling down both vertically and horizontally into your data allows you to not only answer the questions you know you have, but shed slight on those unknown-unknowns and enables associations to make better decisions.

 SS 2 Filtered on Type 2

The Analytics Convergence

Data-guided decisions permeate our everyday lives as individuals, but how can you harness that power for your association and your members? The field of data analytics and big data is exploding with opportunity. Businesses are encroaching on the areas that used to be the private domain of associations – content, networking, events, etc. – because they are employing the power of analytics. But now, the process and tools needed to analyze and interpret data are much less expensive and easier to use than before. Are you ready to have a conversation with your data? Each level of business intelligence has a unique language to make your data speak!
The following presentation was created by Debbie King, CEO of DSK Solutions, Inc. and David DeLorenzo, CIO National League of Cities. This information was first featured at the 2013 ASAE Finance, HR, and Business Operations Conference.

Business Intelligence Trends 2013

Although the term “Business Intelligence” is so overused that it is almost meaningless, what is important to know is that advances in data science and analytics are affecting everyone – every day.  Tableau outlines important trends in this field for 2013. What do these trends mean to your association?