Tag Archives: MicroStrategy

Bryan’s BI Blog: MicroStrategy vs Tableau

Readers:

Bryan BrandowBryan Brandow, has posted his second new post on his new blog, Bryan’s BI Blog and it is a doozy. Bryan does an in-depth comparison of MicroStrategy vs. Tableau.

Here is a link to the MicroStrategy vs. Tableau post.

Best Regards,

Michael

 

How Data Blending Affects the Analytical Engine’s Behavior in MicroStrategy (Part 7)

MicroStrategy Analytics PlatformWith the release of MicroStrategy Analytics Enterprise 9.4.1, the Analytical Engine logic has been enhanced with respect to joining data from multiple datasets in a Report Services Document. One of the features that is available with this release is the ability to use objects (e.g., attributes, metrics) from multiple datasets in a single grid in a document.

If an attribute on a grid has elements that can be obtained from multiple datasets used in the document, the elements displayed will be from the global lookup table. Additionally, if one or more of the datasets containing the attribute has missing attribute form data or has different attribute form from the other datasets, the Analytical Engine will follow the rules noted below to compose the final output:

Rule 1:

If there is attribute form with null value, the Analytical Engine will use the non-null form value from other datasets instead of the null form.

Rule 2:

If several datasets have different attribute form information for the attribute element, the Analytical Engine will use the attribute form from the biggest dataset.

Rule 3:

If several datasets have different attribute form information for the attribute element, and those datasets have same number of rows, the Analytical Engine will use the first dataset in the document for the attribute form value (according to the dataset adding sequence).

NOTE: Users should note that the rules are applied for each individual attribute element in the result at the row level rather than at the dataset level.

Example 1:

Users may consider the following datasets – C01 is a dataset with Customer City, Customer and Order:

Part 7 - 1a

 

C02 is a dataset with Customer, Order and a profit metric. Users may note that the Customer attribute is missing the DESC form in the second dataset:

Part 7 - 2a

If a Report Services Document is built with both these datasets, and the attributes are placed on a grid, the following results may be seen. As noted in Rule 1, the Analytical Engine will display the non-Null values from C01 for the Customer attribute elements:

Part 7 - 3a

Example 2:

Now users may consider a different dataset as C02 – similar to the initial dataset, but here the Customer name (DESC) form contains values instead of NULLs. This time the values for the attributes are not consistent – see that Customer ID ‘1’ has different values for the DESC form for different Orders (1 & 6).

Customer Name Customer ID Order Profit
Customer D 1 1 100
Customer B 2 2 200
Customer C 3 3 300
Xia D 4 4 400
Kris Du 5 5 500
Customer A 1 6 610
Customer E 2 7 720
Customer F 6 8 860
Customer G 7 9 970
Customer H 8 10 1080

If a report is built for this dataset users will observe that the first attribute element value in the dataset is used as as the DESC form for the Orders 1 & 6 even if the value is different in subsequent rows (this is the same as previous Analytical Engine behavior). Part 7 - 5

When these datasets are used in the grid in a Report Services Document, the Analytical Engine will choose the attribute element values from dataset C02 to display in the attribute element values from. This is because of Rule 2 explained above.

Part 7 - 6a

Example 3:

Consider the following dataset:

Customer Name Customer ID Order Profit
Customer D 1 1 100
Customer E 2 7 720
Xia D 4 4 400
Kris Du 5 5 500
Customer G 7 9 970

A report built off this dataset appears as follows:

Part 7 - 8a

After replacing the dataset ‘C02‘ from the previous example with the new dataset, the following results are seen. As noted in Rule 3, because both C01 an C02 have the same number of rows, the elements displayed for the Customer attribute will be filled from from the first dataset to be added to the document – in this case C01. However for the first row in the results, where there is no corresponding customer in the dataset C01, Rule 1 will be applied and instead of a NULL value, the non-null Customer Name field ‘Customer G’ is picked from C02. (Rules are applied at the individual element level).

Part 7 - 9a

Next: Why are some metric values blank in documents using multiple datasets in MicroStrategy Analytics Enterprise 9.4.1

———————————————————————————-

References:

[1] MicroStrategy Knowledgebase, Engine behavior for grids on a Report Services Document or dashboard with multiple datasets where some attribute forms are missing or have different values the datasets in MicroStrategy Analytics Enterprise 9.4.1 and newer releases, TN Key: 45463, 03/13/2014, https://resource.microstrategy.com/support/mainsearch.aspx.

NOTE: You may need to register to view MicroStrategy’s Knowledgebase.

An Introduction to Data Blending – Part 6 (Data Blending using MicroStrategy)

Readers:

In Part 5 of this series on data blending, we reviewed Tableau’s Data Blending Architecture. With Part 5, I have wrapped up the Tableau portion of this series.

I am now going to post, over the next week or so, several parts discussing how we do data blending using MicroStrategy. Fortunately, MicroStrategy just publish a nice technical note on their Knowledgebase (TN Key: 46940) [1] discussing this. Most of what I am sharing today is derived from that technical note.

I probably will have 2-4 parts for this topic in my Data Blending series including how the MicroStrategy Analytical Engine deals with multiple datasets.

I want to thank Kristi Morton (et al) for the wonderful research paper she wrote at The University of Washington [2]. It helped me provide some real insight into the topic and mechanics of data blending, particularly with Tableau. You can learn more about Ms. Morton’s research as well as other resources used to create this blog post by referring to the References at the end of the blog post.

So let’s now dig into how MicroStrategy provides us data blending capabilities.

Best Regards,

Michael

Data Blending using MicroStrategy

In Part 6, we will begin examining using data blending in MicroStrategy. We will first look at how to use attributes from multiple datasets in the same Visual Insight dashboard and link them to existing attributes using the Data Blend feature in MicroStrategy Analytics Enterprise Web 9.4.1.

Prior to v9.4.1 of MicroStrategy, data blending was referred to as Cube Joining.

In MicroStrategy Analytics Enterprise Web 9.4.1, the new Report Services Documents Engine automatically links common attributes using the modeled schema whenever possible. The manual linking is not allowed between different modeled attributes. Just in case the requirement needs to link different attributes, this can be done by using MicroStrategy Architect at the schema level. The join behavior by default for linking related attributes is done using a full outer join. In case there is no relationship between the attributes, then a cross join is used.

The manual attribute linking can be done as shown in the images below.

Part 6 - 1

 

2. Browse the file to match the existing data and select Continue.

Part 6 - 2

 

3. Set the attribute forms if needed. MicroStrategy will automatically assign the detected ones.

Part 6 - 3

4. The attributes can be mapped manually by selecting Link to Project Attribute.

Part 6 - 4

5. Select the attribute form that matches the desired join:

Part 6 - 5

6. The attribute should appear similar to the ones existing in the schema as shown below.

Part 6 - 6

 

7. Save the recently created dataset.

Part 6 - 7

8. Now there are two cubes used as datasets in the same Visual Insight dashboard, as shown below.

Part 6 - 7a

Automatic Linking

The attributes icons now have a blue link, as shown below. This indicates that MicroStrategy has automatically linked them to elements in the Information dataset.

Part 6 - 8

Next: How Data Blending Affects the Analytical Engine’s Behavior in MicroStrategy

———————————————————————————-

References:

[1] MicroStrategy Knowledgebase, How to use attributes from multiple datasets in the same Visual Insight dashboard and link them to existing attributes using the Data Blend feature in MicroStrategy Analytics Enterprise Web 9.4.1, TN Key: 46940, 04/24/2014, https://resource.microstrategy.com/support/mainsearch.aspx.

NOTE: You may need to register to view MiroStrategy’s Knowledgebase.

[2] Kristi Morton, Ross Bunker, Jock Mackinlay, Robert Morton, and Chris Stolte, Dynamic Workload Driven Data Integration in Tableau, University of Washington and Tableau Software, Seattle, Washington, March 2012, http://homes.cs.washington.edu/~kmorton/modi221-mortonA.pdf.

MicroStrategy World 2014: Facebook CIO Tim Campos Keynote Presentation

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Facebook CIO Tim Campos

MicroStrategy World 2014: Gucci CIO Simone Pacciarini Keynote Presentation

Click on Image to Watch PresentationGucci CIO Simone Pacciarini

Michael Saylor’s MicroStrategy World 2014 Keynote Presentation

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PRIME: MicroStrategy Announces Release of Cloud Based, In-Memory Analytics Service, Running at Multi-Terabyte Scale

MicroStrategy Cloud’s New Parallel Relational In-Memory Engine (PRIME) Provides High Performance On Big Data Allowing Companies to Build High-Scale, Easy-to-Use Information Driven Apps

Las Vegas, NV, January 28, 2014 – MicroStrategy® Incorporated (Nasdaq: MSTR), a leading worldwide provider of enterprise software platforms, today announced the availability of its new Parallel Relational In-Memory Engine (PRIME) option for the MicroStrategy Cloud™ at its annual user conference, MicroStrategy World 2014, in Las Vegas. MicroStrategy PRIME™ is a massively scalable, cloud-based, in-memory analytics service designed to deliver extremely high performance for complex analytical applications that have the largest data sets and highest user concurrency. Facebook has successfully built high value information-driven applications with the technology that powers MicroStrategy PRIME.

“Rising data volumes are fueling demand for compelling, easy-to-use analytical applications with the power to revolutionize existing business processes for thousands or tens of thousands of employees, customers, or partners,” said Michael Saylor, CEO, MicroStrategy Incorporated. “MicroStrategy PRIME has been built from the ground up to support the engineering challenges associated with development of these powerful new information-driven apps. This innovative service will allow organizations to derive maximum value from their information by making their Big Data assets actionable.”

Most organizations struggle to harness the value of the information in their Big Data stores due to poor performance. Big Data technologies can store large amounts of information, but distributing that information in an interactive manner to thousands of users with existing commercially available technologies is a huge challenge, often resulting in risky, multi-year projects. MicroStrategy PRIME breaks new ground by tightly coupling a state-of-the art visualization and dashboarding engine with an innovative massively parallel in-memory data store. This architecture allows companies to build highly interactive applications that deliver responses to hundreds of thousands of users in a fraction of the time and cost of other approaches. MicroStrategy PRIME acts as a performance accelerator, opening up the data in databases to a much larger user population, driving new demand for information.

MicroStrategy PRIME combines:

  • Massively parallel, distributed, in-memory architecture for extreme scale. MicroStrategy PRIME is built on an in-memory, highly distributed, massively parallel architecture, designed to run on cost effective commodity hardware. Complex analytics problems can be partitioned across hundreds of CPU cores and nodes to achieve unprecedented performance. MicroStrategy has worked closely with leading hardware vendors to take full advantage of today’s multi-core, high memory servers.
  • Tightly integrated dashboard engine for beautiful, easy-to-use applications. MicroStrategy PRIME includes a state-of-the-art dashboard and data exploration engine, built on the MicroStrategy Analytics Platform™. The visualization engine includes hundreds of optimizations designed specifically for the in-memory data store. This engine enables customers to build complete, immersive applications that deliver high-speed response.
  • Cloud-based delivery for rapid deployment. MicroStrategy PRIME is available as a service on MicroStrategy Cloud, MicroStrategy’s world-class Cloud Analytics platform. MicroStrategy Cloud offers a complete service, including the infrastructure, people and processes to enable customers to quickly and easily develop and deploy high-scale, information-driven applications.

About MicroStrategy Incorporated

Founded in 1989, MicroStrategy (Nasdaq: MSTR) is a leading worldwide provider of enterprise software platforms. The Company’s mission is to provide the most flexible, powerful, scalable and user-friendly platforms for analytics, mobile, identity and loyalty, offered either on premises or in the cloud.

The MicroStrategy Analytics Platform™ enables leading organizations to analyze vast amounts of data and distribute actionable business insight throughout the enterprise. Our analytics platform delivers reports and dashboards, and enables users to conduct ad hoc analysis and share their insights anywhere, anytime. MicroStrategy Mobile™ lets organizations rapidly build information-rich applications that combine multimedia, transactions, analytics, and custom workflows. The MicroStrategy Identity Platform™ (branded as MicroStrategy Usher™) provides organizations the ability to develop a secure mobile app for identity and credentials. The MicroStrategy Loyalty Platform™ (branded as MicroStrategy Alert) is a next-generation, mobile customer loyalty and engagement solution. To learn more about MicroStrategy, visit www.microstrategy.com and follow us on Facebook and Twitter.

MicroStrategy, MicroStrategy Analytics Platform, MicroStrategy Mobile, MicroStrategy Identity Platform, MicroStrategy Loyalty Platform, MicroStrategy Usher, MicroStrategy Cloud and MicroStrategy PRIME are either trademarks or registered trademarks of MicroStrategy Incorporated in the United States and certain other countries. Other product and company names mentioned herein may be the trademarks of their respective owners.

MicroStrategy to focus on customers, not ‘PowerPoint slides,’ at MicroStrategy World conference

Source: Chris Kanaracus, IDG News Service, PCWorld, Business & Finance Software

Paul Zolfaghari
President, MicroStrategy

While some vendor conferences can end up mired in technical minutiae, MicroStrategy believes it’s better to show, not tell customers how its BI (business intelligence) software works, according to its president, Paul Zolfaghari.

”More than 50 MicroStrategy customers will deliver presentations at the event, which has about 130 sessions planned in total, according to a statement. They include BMC Software, Flextronics, Nielsen, Panda Restaurant Group and Publicis Touchpoint Solutions.

Scheduled for keynotes are Facebook CIO Tim Campos and Gucci CIO Simone Pacciarini, who will discuss their use of Microstrategy technology.When it does discuss products at the event, Microstrategy plans to showcase its recently released Analytics Desktop, a self-service BI tool that is available at no charge, as well as its push into mobile BI, Zolfaghari said.

Mobility has transformed the BI market, in Zolfaghari’s view. Five or six years ago, companies largely ran some internal reports and rolled the results up the corporate food chain, he said. “What’s happened is BI has now moved massively outside of HQ.”

It’s also likely MicroStrategy will discuss the massively parallel in-memory computing architecture it’s been working on with Facebook. The technology should be commercially available from MicroStrategy later this year, showing up first in MicroStrategy’s cloud BI offering, according to Zolfaghari.

The conference comes as MicroStrategy, the industry’s last remaining large pure BI vendor, faces ever-stiffer competition from platform companies such as Oracle and SAP, as well as upstarts like Tableau and Birst.

But MicroStrategy is keeping an edge thanks to a number of key strategic decisions, according to a recently released Forrester Research report on the BI market.

”MicroStrategy has grown organically and architected its entire suite as a single platform,” analyst Boris Evelson wrote. “Forrester clients find that, after making the initial investment and effort in MicroStrategy, the reusability of all objects and the relational OLAP engine with drill-anywhere capability often result in a lower long-term total cost of ownership.”

Forrester clients are also having success rolling out mobile BI based on MicroStrategy’s platform, Evelson said.

But there’s some cause for concern over MicroStrategy’s “high reliance on a largely disappearing network of partners, many of which have been acquired,” for architectural components such as ETL (extract, transform and load), data quality and MDM (master data management), Evelson added.

Zolfaghari downplayed the impact of its partners being acquired, noting that Informatica, a major provider of such tools, remains independent. MicroStrategy also maintains “robust relationships” with companies such as IBM, SAP and Oracle, he said.

MicroStrategy World runs from Jan. 27-30.

Chris Kanaracus covers enterprise software and general technology breaking news for the IDG News Service. More by

Has MicroStrategy Toppled Tableau as the Analytics King?

MicroStrategy Analytics

In a recent TDWI article titled Analysis: MicroStrategy’s Would-Be Analytics King, Stephen Swoyer, who is a technology writer based in Nashville, TN, stated that business intelligence (BI) stalwart MicroStrategy Inc. pulled off arguably the biggest coup at Teradata Corp.’s recent Partners User Group (Partners) conference, announcing a rebranded, reorganized, and — to some extent — revamped product line-up.

One particular announcement drew great interest: MicroStrategy’s free version of its discovery tool — Visual Insight — which it packages as part of a new standalone BI offering: MicroStrategy Analytics Desktop.

With Analytics Desktop, MicroStrategy takes dead aim at insurgent BI offerings from QlikTech Inc., Tibco Spotfire, and — most particularly — Tableau Software Inc.

MicroStrategy rebranded its products into three distinct groups: the MicroStrategy Analytics Platform (consisting of MicroStrategy Analytics Enterprise version 9.4 — an updated version of its v9.3.1 BI suite); MicroStrategy Express (its cloud platform available in both software- and platform-as-a-service  subscription options; and MicroStrategy Analytics Desktop (a single-user, BI discovery solution). MicroStrategy Analytics Enterprise takes a page from Tableau’s book via support for data blendinga technique that Tableau helped to popularize.

“We’re giving the business user the tools to join data in an ad hoc sort of environment, on the fly. That’s a big enhancement for us. The architectural work that we did to make that enhancement work resulted in some big performance improvements [in MicroStrategy Analytics Enterprise]: we improved our query performance for self-service analytics by 40 to 50 percent,” said Kevin Spurway, senior vice president of marketing with MicroStrategy.

Spurway — who, as an interesting aside, has a JD from Harvard Law School — said MicroStrategy implements data blending in much the same way that Tableau does: i.e., by doing it in-memory. Previous versions of MicroStrategy BI employed an interstitial in-memory layer, Spurway said; the performance improvements in MicroStrategy Analytics Enterprise result from shifting to an integrated in-memory design, he explained.

“It’s a function of just our in-memory [implementation]. Primarily it has to do with the way the architecture on our end works: we used to have kind of a middle in-memory layer that we’ve removed.”

Spurway described MicroStrategy Desktop Analytics as a kind of trump card: a standalone, desktop-oriented version of the MicroStrategy BI suite — anchored by its Visual Insight tool and designed to address the BI discovery use case. Desktop Analytics can extract data from any ODBC-compliant data source. Like Enterprise Analytics, it’s powered by an integrated in-memory engine.

In other words: a Tableau-killer.

“That [Visual Insight] product has been out there but has always been kind of locked up in our Enterprise product,” he said, acknowledging that MicroStrategy offered Visual Insight as part of its cloud stack, too. “You had to be a MicroStrategy customer who obviously has implemented the enterprise solution, or you could get it through Express, [which is] great for some people, but not everybody wants a cloud-based solution. With [MicroStrategy Desktop Analytics], you go to our website, download and install it, and you’re off and running — and we’ve made it completely free.”

The company’s strategy is that many users will, as Spurway put it, “need more.” He breaks the broader BI market into two distinct segments — with a distinct, Venn-diagram-like area of overlap.

“There’s a visual analytics market. It’s a hot market, which is primarily being driven by business-user demand. Then there’s the traditional business intelligence market, and that market has been there for 20 years. It’s not growing as quickly, and there’s some overlap between the two,” he explained.

“The BI market is IT-driven. For business users, they need speed, they need better ways to analyze their data than Excel provides; they don’t want impediments, they need quick time to value. The IT organization cares about … things … [such as] traditional reporting [and] information-driven applications. Those are apps that are traditionally delivered at large scale and they have to rely on data that’s trusted, that’s modeled.”

If or when users “need more,” they can “step up” to MicroStrategy’s on-premises (Enterprise Analytics) or cloud (Express) offerings, Spurway pointed out. “The IT organization has to support the business users, but they also need to support the operationalization of analytics,” he argued, citing the goal of embedding analytics into the business process. “That can mean a variety of things. It can mean a very simple report or dashboard that’s being delivered every day to a store manager in a Starbucks. They’re not going to need Visual Insight for something like that — they’re not going to need Tableau. They need something that’s simplified for everyday usage.”

MicroStrategy Analytics Powerful

Something More, Something Else

Many in the industry view self-service visual discovery as the culmination of traditional BI.

One popular narrative holds that QlikTech, Tableau, and Spotfire helped establish and popularize visual discovery as an (insurgent) alternative to traditional BI. Spurway sought to turn this view on its head, however: Visual discovery, he claimed, “is a starting point. It draws you in. The key thing that we bring to the table is the capability to bridge the gap between traditional model, single-version-of-the-truth business intelligence and fast, easy, self-service business analytics.”

In Spurway’s view, the usefulness or efficacy of BI technologies shouldn’t be plotted on a linear time-line, e.g., anchored by greenbar reports on the extreme left and culminating in visual discovery on the far right. Visual discovery doesn’t complete or supplant traditional BI, he argued, and it isn’t inconceivable that QlikTech, Tableau, and Spotfire — much like MicroStrategy and all of the other traditional BI powers that now offer visual discovery tools as part of their BI suite — might augment their products with BI-like accoutrements.

Instead of a culmination, Spurway sees a circle — or, better still, a möbius strip: regardless of where you begin with BI, at some point — in a large enough organization — you’re going to traverse the circle or (as with a möbius strip) come out the other side.

There might be something to this. From the perspective of the typical Tableau enthusiast, for example, the expo floor at last year’s Tableau Customer Conference (TCC), held just outside of Washington, D.C. in early September, probably offered a mix of the familiar, the new, and the plumb off-putting. For example, Tableau users tend to take a dim view of traditional BI, to say nothing of the data integration (DI) or middleware plumbing that’s associated with it: “Just let me work already!” is the familiar cry of the Tableau devotee. However, TCC 2013 played host to several old-guard exhibitors — including IBM Corp., Informatica Corp., SyncSort Inc., and Teradata Corp. — as well as upstart players such as WhereScape Inc. and REST connectivity specialist SnapLogic Inc.

These vendors weren’t just exhibiting, either. As a case in point, Informatica and Tableau teamed up at TCC 2013 to trumpet a new “strategic collaboration.” As part of this accord, Informatica promised to certify its PowerCenter Data Virtualization Edition and Informatica Data Services products for use with Tableau. In an on-site interview, Ash Parikh, senior director of emerging technologies with Informatica, anticipated MicroStrategy’s Spurway by arguing that organizations “need something more.” MicroStrategy’s “something more” is traditional BI reporting and analysis; Informatica’s and Tableau’s is visual analytic discovery.

“Traditional business intelligence alone does not cut it. You need something more. The business user is demanding faster access to information that he wants, but [this] information needs to be trustworthy,” Parikh argued. “This doesn’t mean people who have been doing traditional business intelligence have been doing something wrong; it’s just that they have to complement their existing approaches to business intelligence,” he continued, stressing that Tableau needs to complement — and, to some extent, accommodate — enterprise BI, too.

“From a Tableau customer perspective, Tableau is a leader in self-service business intelligence, but Tableau [the company] is very aware of the fact that if they want to become the standard within an enterprise, the reporting standard, they need to be a trusted source of information,” he said.

Among vendor exhibitors at TCC 2013, this term — “trusted information” or some variation — was a surprisingly common refrain. If Tableau wants to be taken seriously as an enterprisewide player, said Rich Dill, a solutions engineer with SnapLogic, it must be able to accommodate the diversity of enterprise applications, services, and information resources. More to the point, Dill maintained, it must do so in a way that comports with corporate governance and regulatory strictures.

“[Tableau is] starting to get into industries where audit trails are an issue. I’ve seen a lot of financial services and healthcare and insurance businesses here [i.e., at TCC] that have to comply with audit trails, auditability, and logging,” he said. In this context, Dill argued, “If you can’t justify in your document where that number came from, why should I believe it? The data you’re making these decisions on came from these sources, but are these sources trusted?”

Mark Budzinski, vice president and general manager with WhereScape, offered a similar — and, to be sure, similarly self-serving — assessment. Tableau, he argued, has “grown their business by appealing to the frustrated business user who’s hungry for data and analytics anyway they can get it,” he said, citing Tableau’s pioneering use of data blending, which he said “isn’t workable [as a basis for decision-making] across the enterprise. You’re blending data from all of these sources, and before you know it, the problem that the data’s not managed in the proper place starts to rear its ugly head.”

Budzinski’s and WhereScape’s pitch — like those of IBM and Teradata — had a traditional DM angle. “There’s no notion of historical data in these blends and there’s no consistency: you’re embedding business rules at the desktop, [but] who’s to say that this rule is the same as the [rule used by the] guy in the next unit. How do you ensure integrity of the data and [ensure that] the right decisions were made? The only way to do that is in some data warehouse-, data mart-[like] thing.”

Stephen Swoyer can be reached at stephen.swoyer@spinkle.net.

Data Archaeology Selected as One of the 2014 MicroStrategy World Dashboard Contest Winners

Click here to learn more about MicroStrategy World 2014Hello Readers:

Data Archaeology, Inc.I just found out I am one of the 2014 winners of the MicroStrategy World Dashboard Contest. I was also one of the winners last year.

I get a free pass to MicroStrategy World in Las Vegas which is the last week of this month. Last year, they gave us awards too. Not sure yet if they will do the same this year.

An Exploration of Tax Data

My dashboard is an exploration of tax data. It explores taxes rates for the top ten counties in terms of GDP.

I used horizontal stacked bar charts instead so that the viewer can visually see how social security and income tax rate add up to the total and explains visually why the countries are ordered the way they are on the dashboard. I also separated out $100K and $300K percentages into separate visuals.

In addition, I added the flags of the countries. Yes, I know, chart junk!

Now, you don’t see any numbers on the data points in this dashboard. The reason you don’t see them is because they appear when you mouse over a bar where you then see the country, category and the percent value as a tooltip.

Here is a screenshot of my entry. It was written with MicroStrategy v9.3.1, Report Services and the Visualization SDK.

Best regards,

Michael

Click on image to enlarge

DA_An_Exploration_of_Tax_Data

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