Business iQ Enhancements in 4.5: Connecting the dots between applications and business

Digital transformation has brought applications into the limelight. The importance of application performance monitoring has grown many-folds and application and business correlation is more critical than ever. Applications are the touch-points between businesses and the end-users, and therefore, influence the business strategy.

Business iQ, the business performance monitoring solution from AppDynamics, helps our customers correlate application performance with critical business metrics in real-time. The focus on providing these real-time insights in an uncomplicated, easily operable manner is a theme persistent across our product releases. In 4.5 as well, released in July 2018, our team focused on delivering solutions that are easy to use and solve key business performance issues.

Improved Business Correlation

Business Journeys was released in 4.4, in Nov 2017, and provides end-to-end visibility into multi-step complex business workflows by stitching them together through unique identifiers. In 4.5, we provide out-of-the-box dashboards and metrics with no manual configuration required. These dashboards provide aggregate view of the key data points such as average total time, average wait time between milestones, conversion, number of events per milestone etc. for all the business journeys. An example of a loan application approval business journey is shown below.

Out-of-the-box metrics on business journeys allow users to create health rules and alerts to track deviations from the normal business workflow. These metrics can be compared with past data using machine-learning based dynamic baselines. The screenshot below compares the average total time for loan approval in the last hour with the last 15 days baselined data.

We also added support for custom data sources to the configuration and one-click access from aggregate view to the underlying event data – all these enhancements focused on providing more business insights with just few clicks.

Experience level management (XLM) allows users to monitor and report on key service levels and end-user experience levels critical to delivering high-performing applications. Since these experience levels and service levels differ based on geographies, time zone support for such reports is a must-have requirement. XLM configuration now supports different time zones. For e.g. United Airlines can now track the login response time separately for East Coast and West Coast, or for North America and Europe.

Business iQ’s analytics and reporting capabilities are powered by AppDynamics Query Language (ADQL) and UI widgets.

Additional ADQL Operators

New ADQL operators, HAVING, and SINCE..UNTIL, enable more sophisticated aggregation and filtering. The HAVING clause is used to filter groups created by aggregate functions such as SUM or AVG as the WHERE clause cannot be used with these aggregate functions. For example in a financial application, to list the business transactions with average response time greater than 5000 ms.

SINCE..UNTIL makes it easier for the user to select specific time window in the ADQL search query and not get tied to the UI based time picker. For example, the following search query can be used to return all events from Black Friday by using unix/epoch time for Nov 24, 2017

SELECT * FROM transactions SINCE 1511510400 UNTIL 1511596800

Or use the following query to simply search for events from the last one hour

SELECT * FROM transactions SINCE 1 hour

Widgets Enhancements

Enhancements to our widgets allows more precise widget customization and make it easier to interpret trends in your event data. Log axis for time series widgets, level of significance and trailing period comparison for numeric widgets along with other enhancements enable users to compare and highlight metrics that are most important.

Business Metrics

Business Metrics are used to monitor values of certain repetitive ADQL searches such as per minute data on the number of customers impacted by the slowness in a login application. The Metric Listing page has been updated to provide a more intuitive experience. Click on a metric name to open a pre-populated Metric Browser or select multiple metrics to view them together in the Metric Browser for comparison. The Metric page now displays the underlying ADQL query for metrics, making it easy to see what a particular metric represents and how it is calculated.

Greater Scale

On our underlying Platform, called the Event Service, we continue to make improvements to our existing architecture to ensure maximum uptime, real-time availability of data, and blazing fast query response time. This will allow our platform to scale to even greater heights, ingest more events, and respond to queries at the performance AppDynamics users can expect.

Agentless Analytics

We are also excited to launch a Beta program for using Transaction Analytics without the need to install an additional Analytics Agent and enable analytics data collection with the snap of a finger.

The focus of product teams at AppDynamics is to deliver easy to use solutions providing key application and business performance insights. This cannot be achieved without the valuable feedback from our customers. Feel free to reach out to your AppDynamics account team to share your thoughts and to learn more about what’s new in 4.5 or what’s coming in near future.

Louis Huard and Stefan Hermanek also contributed to this blog post. 

Improve the Productivity of Relationship Managers and Financial Advisors with Business iQ

Every job has its mundane administrative tasks, and we all hate them. In the world of wealth management, relationship managers are pressured to serve as many existing customers and prospects as they can with the ultimate goal of increasing the assets under management (AUM)—one of the key metrics used to measure their productivity. Similarly, in the insurance industry, financial advisors are driven to maximize their time with clients. Administrative tasks are not only irritating, they also reduce a salesperson’s paycheck by cutting into his or her time with customers.

But organizational forces in both the wealth management and insurance industries are conspiring against their top revenue generators. According to Seismic, a staggering 65% of a relationship manager’s time is spent on business processes like account opening, accessing collaterals, and creating customized portfolio review with customers.

In the last few years, financial institutions and insurance companies have sought to free up their salespeople by investing in productivity tools. Mobile apps, in particular, hold the promise of speeding up processes like filling out client forms for clients, creating proposals, and building portfolios. They are also, in theory, a great way to deliver real-time market insights.

But mobile apps are only effective when relationship managers and advisors use them.

AppDynamics Business iQ allows organizations to measure the effectiveness of their mobile apps by providing a window into user behavior. In the example below, I show how a financial institution can instantly see how many relationship managers have clicked on a market insight to access AI-driven financial advice—a killer feature for increasing AUM. The dashboard, which I created in the AppDynamics demo environment, also shows how many relationship managers proceeded to “Add to Cart” and re-balanced their clients’ portfolios. We see that as relationship managers moved through the funnel, they increasingly abandoned the app. The overall conversion rate is just 5.62%. Slightly over one in twenty relationship managers used the application to send a proposal to their clients.

Below, I show how to a create conversion funnel using a built-in widget. It is as simple as going to the Add Widget tab and selecting Analytics and Funnel Analysis.

 You then select the business transaction that you’d like to include in the conversion funnel.

You can also quickly design a custom widget to highlight information such as the relationship managers who are generating the most new business.

Figure:  RMs with the highest new AUM

Or see at a glance the relationship managers who are sending the highest number of proposals. Moreover, you can break down the proposals by customer type. So you can see which customer type (Silver, Gold, Platinum, Diamond) the relationship managers are creating the proposals for. In the example below, you can see that relationship manager “aleftik” is sending all 960 proposals to only “Silver” tier customers. Relating the previous graph where the highest AUM is “aleftik” and he focuses all his effort to selling to the “Silver” tier customers, it appears that this is a desirable behaviour and strategy that the business should educate and share among other relationship managers.

Figure: RMs with the highest “Send Proposal” Transactions

Moving beyond the performance metrics of individual relationship managers and financial advisors, you can combine technical and performance metrics in order to see if updates to an application are negatively affecting sales performance.

You can see from the above conversion graph that version 2 of the code has significantly reduced the slowness (yellow and orange color within the bar) for Portfolios Summary page, positively impacting the conversion ratio from 5.53% to 14.52%

The business may also want to identify relationship managers who are not using the new productivity tool enough. Below is a way to create such a list of managers with the least number of page hits.

Figure: Number of page visit on “Market Insights” by RMs in ascending order

You can even put all of this together to have a customizable dashboard combining both technical and business performance metrics. At a glance you’re able to see the new AUM achieved by the wealth management group using the iPad application, transaction health of each key business process, top performing relationship managers and the products sold, as well as relationship managers who have yet to adopt the new application as a productivity tool.

With AppDynamics Business iQ, institutions do not need to wait for a month or a week to see business insights in relation to application performance and user behaviour. All the information is available at a glance in real time.

Monitor End-User Experience Levels and Service Availability with eXperience Level Management (XLM)

Digitization has transformed the way customers buy and use products. There has been a tectonic shift in customer expectations regarding product availability (measured by service level management) and product performance (measured by experience level management).

According to a 2017 State of Online Retail Performance report by SOASTA (now part of the content delivery network provider, Akamai), 53% of mobile site visitors leave a page that takes longer than three seconds to load (based on data equating to approximately 10 billion user visits). Another study ties customer satisfaction to website performance by highlighting the fact that only 38% of users stated website availability as an issue, whereas around 73% of users complained about slow website experience.

The difference between the percent of customers impacted by service levels vs. those affected by experience levels is enormous and brings to the fore a critical question: Can enterprises now only rely on service availability to deliver the best customer experience? The answer is, no.

Customers now have a high bar for technical performance and certain service levels, making Service Level Monitoring insufficient for enterprises looking to offer best-in-class end-user experience. Companies now need to consider end-user experience levels (to measure the efficiency and effectiveness of the service) as the key metric, and service levels (for availability and resolution) as a contributing factor to the end-user experience.

Challenges with eXperience Level Management

In the past, instrumenting end-user eXperience Level Management (XLM) has not been straightforward for any business.

One huge challenge in implementing XLM is ascertaining the data sources for compliance calculations. Businesses spend hours and days gathering all the data in spreadsheets and other tools in an attempt to feed the right data into their policy management applications. But the myriad of data collection mechanisms, with different data formats and user workflow definitions, result in an inaccurate XLM policy implementation often based on erroneous data.

And all this trouble is for a single SLA policy addressing a single product and user type. An enterprise with multiple products can’t even consider identifying the right experience level for their different products and customer segments because of this extremely complex and tedious process. Without being able to segment experiences, an important customer’s experience might get rolled up with everyone else’s, and their challenges might have a disproportionate impact on your business. For example, a delay in delivering a product for an Amazon prime member who has indicated shipping speed as a priority could result in a loss in future business.

Another challenge in deriving a proper XLM solution in an enterprise is establishing a “single source of truth” between all parties involved in an application. End-users may have one set of expectations for where they engage, while third-party service providers might have another, and some of these expectations may be expressed contractually, too. As an enterprise, straightforward communication throughout the business is key to establishing trust between all stakeholders and ensuring all agreements are being met.

AppDynamics launches XLM in Nov 2017

We at AppDynamics are excited to address these challenges for our customers with the introduction of eXperience Level Management (XLM) as part of our Business iQ product. XLM provides an ability to measure metrics that matter to businesses and their end-users, along with the ability to measure service availability.

Automated data collection and reporting, single source of data, experience levels for different product types and customer segments, and an immutable audit trail to build trust amongst all parties – AppDynamics’ XLM solves these main challenges that enterprises face in implementing their business-critical experience and service-level policies.

Data Selection with Exclusion Periods

AppDynamics Business iQ collects every bit of information flowing through an end-to-end application workflow, and can ingest data from multiple data sources. These could be events generated by AppDynamics agents like business transaction events, log events, or end-user events. These could also be events that are sent to Business iQ using REST APIs or other custom events such as Business Journeys (released in 4.4) that defines complex business workflows. An XLM report can be created on any of these event types for end-user experience management and service availability calculations.

What’s more, for any planned upgrades or maintenance schedules that can lead to potential degradations in end-user experience, XLM has the functionality to explicitly define exclusion periods to disregard compliance calculations during such intervals – ensuring that trivial data collection is excluded.

Compliance Target and Daily Thresholds

Once the data set is defined, users can set compliance targets on any business or application metric that is key to their business or end-users. These metrics can be anything from login time for gold member airline customers, to the checkout time for platinum customers on an e-commerce website.

XLM provides users the ability to define different threshold levels (Normal, Warning, and Critical) to monitor their reports. By providing multiple thresholds, XLM enables users to visualize slight degradations within their metrics and take prompt corrective actions.

XLM Configuration Settings.

Users can also specify reporting period (weekly or monthly) to define aggregation intervals and view the compliance on the aggregated data. XLM also has a drill-down functionality, allowing users to take weekly or monthly data and drill down to daily data and even as granular as individual events.

XLM Dashboard – with aggregate view of compliance for the last five periods

Car Loan Login Response Time – Daily Compliance Data for a weekly aggregate with drill-down to event level information.

Audit Trail

Lack of trust is one of the challenges for all parties involved in monitoring, implementing, and enforcing compliance. With fully automated data collection and reporting for XLM, and an immutable audit trail of any changes made to the configuration, AppDynamics can be that “single source of truth” for our customers and their partners.

Audit trail for “Car Loan Login Response Time” XLM report.

While the consistency in service availability is vital, businesses need to provide the best quality experience tailored to the product and customer segment. eXperience Level Management (XLM) is the first step towards helping our customers achieve this. We look forward to your comments and feedback.

Learn more about Business iQ or schedule a demo to learn more about AppDynamics.

Accelerate Your Digital Business with AppDynamics Winter ‘17 Product Release

Last month at AppD Summit New York, we unveiled the latest innovations in our Business iQ and App iQ platforms, paving the way for a new era of the CIO and digital business. Delivering on this vision, we’re excited to announce the general availability of AppDynamics’ Winter ‘17 Release for our customers.

As application and business success become indistinguishable, enterprises are increasing their investment in digital initiatives. According to Gartner, 71% of enterprises are actively implementing digital strategies, and IDC predicts that companies will spend $1.2 trillion on their digital transformation in 2017 alone.

But without effective tools to correlate application and business performance – and lack of end-to-end visibility across customer touchpoints, application code, infrastructure, and network – customer experiences and employee productivity are degraded, and executives can’t analyze or justify technology investments. In fact, according to McKinsey, the digital promise still seems more of a hope than a reality, with only 12% of technology and C-level executives confident that IT organizations have been effective in this shift.

Winter ‘17 Release is Here

Business iQ just got better. Bridging the gap between the app and the business, BiQ capabilities have expanded to include:

Business Journeys

With AppDynamics Business Journeys, application teams can link multiple, distributed business events into a single process that reflects the way customers interact with the business. Business events can include transaction, log, mobile, browser, synthetics, or custom events and are long-running, from hours to days.

Application teams can create performance thresholds and quickly visualize where performance issues are impacting the customer experience. KPIs for each Business Journey inform technology investments and effectively prioritize code development and release.

In the two figures below, you can see how easy it is to set up a new Business Journey for loan approvals and visualize the impact of delays through the lens of the business.

Business_Journey_Ani_720x.gif

Fig 1: Author an end-to-end Business Journey by joining multiple distributed events.

Screen Shot 2017-10-31 at 11.27.16 AM.png

Fig 2: Quickly and easily create custom dashboards visualizing business performance.

Experience Level Management (XLM)

With XLM, enterprises can establish custom service-level thresholds by customer segment, location, or device. For example, the CIO of a major retailer may deliver tailored experiences to its top customers by setting performance thresholds across its customer channels — including website, mobile apps, in-store wireless, and in-store checkout. XLM also provides an immutable audit for service-level agreements with your customers or internal business units. The product images below show the service levels setup for a connected streaming device, giving an instant view on how services are performing against set SLAs.

Screen Shot 2017-11-01 at 10.45.06 AM.png

Fig 3: Service levels setup for a connected streaming device.

Network Visibility

Application developers, IT Ops  and network teams often work in silos using a myriad of different monitoring tools. To troubleshoot application performance issues, war rooms are created, and the lack of a common language and visibility across different tools results in finger pointing, endless debates, and slower Mean Time to Resolution (MTTR).

With the introduction of AppDynamics Network Visibility, a capability AppDynamics is uniquely positioned to address now as part of Cisco, enterprises will be able to understand the impact that the network is having on application and business performance. Network performance measurements are automatically correlated with application performance in the context of the Business Transaction. IT teams will be able to triage network issues with one single pane of glass and provide the right information to network teams before there is an impact on the end-user experience. Finally, an answer to end-to-end visibility from customer, to code, to network is here.

AppDynamics automatically discovers network devices such as reverse proxy load balancers deployed on-premises and in cloud environments and eliminates the need to use expensive network tools such as SPAN/TAP to capture and analyze network traffic.

The animation below shows out-of-box visibility into network flow maps, network metrics such as latency, throughput, retransmission rates, and critical errors, enabling IT Ops to quickly identify and isolate root cause without the need to engage network teams.

Network_Viz_Ani_720x.gif

Fig 4: Correlated and out-of-box view of network performance in context of application performance.

AppDynamics IoT

IoT devices create another channel to engage with customers, and if properly measured and optimized, can create game-changing business benefits. With new IoT visibility, businesses can convert rich and invaluable insights into consumer behavior, buying patterns, and business impacts. IoT visibility includes:

Device analytics  — Together with Business iQ, IoT visibility provides an unprecedented insight into how IoT devices are driving business impact. And because these insights are delivered through a single platform, IoT visibility is the first and only solution that maps and correlates entire customer journeys — from the device to customer touchpoint, to business conversions.

Device application visibility and troubleshooting — AppDynamics’ new IoT visibility provides an aggregated view into device uptime, version status, and performance, enabling drill-down views into the device to simplify the troubleshooting of IoT applications. The screenshot below shows a list view of all active devices. A simple double-click on a specific device takes you to the device details.

Custom dashboards — Every company measures success differently. With custom dashboards in IoT visibility, companies from any vertical can quickly build new visualizations to measure the business impact of IoT devices — from the revenue impact of a slow checkout for a brick and mortar retailer, to the customer impact of a software change in a connected car.

All_active_devices.png

Fig 5: Consolidated list view of all active smart-shelf  IoT devices and key KPIs.

Synthetic Private Agent

AppDynamics Winter ‘17 Release brings Browser Synthetic Monitoring to your internal network. By running Synthetic Private Agent on-premises, you can monitor the availability and performance of internal websites and services that aren’t accessible from the public Internet. You can also test specific locations within your company and set alerts when performance issues occur and fix them before end-user experience is impacted.

Cross-Controller Federation

As application teams start using microservices architecture, the scalability requirements have exploded, necessitating APM scale. With Cross-Controller Federation, AppDynamics is taking unified monitoring to the next level. Our customers can achieve limitless scalability and flexibility to deploy application components across multiple public and private clouds.

Only with AppDynamics, customers get complete correlated visibility and quick drill-down into the line of code, irrespective of where the application components and controllers are deployed, because controllers can participate in a federation. Another important use case is keeping APM data isolated by deploying multiple controllers yet maintaining correlated visibility for compliance, architecture, and business reasons.

KPI Analyzer

KPI Analyzer applies machine learning to automate root cause analysis. With the KPI analyzer, customers can isolate the metrics that are the most likely contributors to poor performance, and identify the likely degree of impact on the KPI for each metric, automatically. The KPI analyzer makes troubleshooting root cause as simple as clicking a prompt to surface the underlying issue most likely to be the root cause of degraded performance.

The following figure shows KPI Analyzer in action. KPIs such as average response time are displayed with metrics that are automatically identified as the root cause and scored in ranked order for quick resolution.

KPIAnalyzer.png

Fig 6: Key application KPIs and automatically-detected root causes in ranked order.

Learn More

AppDynamics’ Winter ‘17 Release is rich with other important features such as Universal Agent to simplify agent installation and configuration, Enterprise Console for streamlined controller lifecycle management, and Node.js flame graph for deeper visibility, among several other features.

Join us for a webinar on November 16th to get an in-depth look into the latest innovations and features in our Winter ‘17 Release. You can also get started with the free trial of AppDynamics Winter ‘17 today!

Four Use Cases for Leveraging Business iQ

The application and the business have converged.

In fact, the performance of your business is now inseparable from the performance of your apps. Customers who are connected to the code you write or the applications and infrastructure you manage demand a flawless experience, and they are loyal to the brand that delivers it. The challenge, however, is that the traditional ways of managing services and operations are falling short, jeopardizing business success.

Many BI tools today help analyze business data, but they are mostly for historical analysis and trends. Web analytics tools on the other hand help analyze customer conversion rates and how end-users are using your website, but don’t tell you why it’s happening. And then there are traditional APM tools that tell you whether your applications are healthy or performing poorly, but offer little visibility into the impact on your business. As a result, many organizations are struggling to connect data to business outcomes.

Business iQ offers real-time context from customer to code – connecting application performance data to business outcomes to enable both the business and IT.

To see how you can leverage AppDynamics Business iQ, check out these four common use cases.

Business Health

Let’s take a scenario where there is a major event, like Black Friday or a launch day for an important product, or simply any day you need to win customers. If you are using AppDynamics for your APM solution, your DevOps may receive alerts about anomalies in your application’s performance. When this happens, business owners may want to understand the impact on key business drivers, as well as any revenue and customer experience implications. With Business iQ, you can monitor critical business KPIs to get real-time insight into the health of your business.

Figure 1

Using Figure 1 (above), let’s say you are an e-commerce site and manage a number of different brands. Overall, you care about your site’s conversion rate, number of orders processed, total sales, and the percentage of customers moving to your loyalty program.

It can be inferred from the dashboard that in the last hour, ‘Total Sales’ may be declining since not many of your loyal customers are shopping today. What’s more, you can also see from the dashboard that there’s a clear correlation between the drop in sales revenue and the the % errors in APDY Electronics. However, with just a 1% error in APDY Books, there may be a business problem impacting sales versus an IT issue.

With this level of insight, DevOps teams will be able to investigate root-cause for the performance issue, or declare that it’s not an IT problem. Business health monitoring attempts to converge business data with application and infrastructure data to give you visibility into business KPIs that allow you to diagnose and fix problems in real time.

User Journey

Now that we’ve covered business health monitoring, let’s move on to our second use case: User journey monitoring, which measures how business components and customer experience come together to drive top-level KPIs. Figure 2 (below) helps illustrates this use case:

Figure 2

Let’s say you’re a bank that would like to understand how your users are moving along the loan processing journey – from viewing rates online, submitting an application on your website, running a credit check, and finally getting the loan approval.

Business teams might be interested in knowing how many customers are in the loan journey, where there are drop-offs, and how KPIs are impacted. Your operations team, however, may be curious if customer drop-offs are a result of slow application performance. And lastly, from a developer standpoint, you may want to know how you are impacting a larger process and causing real-business impact.

In the above dashboard, you can see that a longer response time during the “Submit Application” step at 7s, is probably causing a higher drop-off, and therefore impacting the loan amount processed at $10M. Furthermore, a 15% error rate at “Credit Check” is further compounding this problem at the “Loan Approval” stage.

User Journey Monitoring allows you to visualize different parts of a process, driving a common language between business and IT, whether you are a bank looking to optimize your processes or a retailer trying to visualize how your customers shop online.

Customer Segment

Interested in understanding the end-to-end experience of your critical customer segments? With Business iQ, you can. Check out the use-case below for customer segment monitoring.

Figure 3

Let’s say you’re a travel company that connects back-end travel inventory (think flights, hotels, etc.) to multiple front-end buying channels (think websites used to book travel, like Expedia, Orbitz, Priceline, etc.) With Business iQ, you can compare customer experience across these various buying channels, and segment customers based on error codes, slow transactions, and more. You can also analyze customer experience across various travel agents or hotel brands.

This deep-level end-user monitoring is critical for businesses, as it allows you to monitor customer issues so you can proactively avoid them in the future.

Your DevOps team might also be interested in customer segment monitoring to understand where to prioritize troubleshooting efforts. For example, by looking at the above dashboard, it’s clear that Priceline customers are experiencing issues with reservation confirmation and search availability, and that the “5 Star Luxury” hotel class segment has the highest error reservations. This information allows DevOps teams to have visibility into how their critical customer segments are performing and prioritize what they want to work on.

This capability allows your business to get visibility into how application performance impacts customer interaction with your features.

Release Validation

You can also use AppDynamics in real-time as you release newer versions of your application, or migrate from a legacy infrastructure to a new infrastructure. Business iQ also allows you to compare KPIs from your previous and current versions.

Figure 4

Let’s consider this example using Figure 4 (above): APDY media has an entertainment site where customers sign up for subscriptions. The journey they go through starts with creating a profile, selecting their favorite content, setting alerts on what content they want to be notified about, and finally, subscription confirmation.

Looking at the above dashboard, it is evident that in Version 1.0 of APDY media, the subscription rate starts to decline significantly, and it appears to be linked to a performance issue when selecting “Favorite Content.”

You can use Business iQ to help identify the problem and understand where to fix the issue. You can also use Business iQ to compare releases and identify if the problems you wanted to fix in your latest release are indeed fixed. You can do this by seeing if performance in the “Favorite Content” step improved post-release and how it correlates to an increase in conversion.

You can also see from this dashboard that while you are sending a smaller amount of traffic to Version 2, you still managed to triple your conversion rate while also driving much higher subscriptions.

The above use cases are just some of the common scenarios we are seeing in our customer environments. As you try our product, you’ll learn that there’s a lot more you can achieve with Business iQ.

Harish Doddala is leading product growth and adoption initiatives of Business iQ at AppDynamics. He has over 10 years of Product Management and Software Engineering experience delivering results for Cisco, VMware, and Oracle.

Is Your Intelligence Failing You in One Critical Area?

How’s your Business Intelligence software working out for you?

If your experience has been like that of many BI users, your answer is probably a bit of a mixed bag. That’s because most BI users have experienced a combo of great insights and extreme frustration from their BI software.

Change is in the air. The reason I want to discuss this today is because as with many things IT, intelligence is up for disruption as well.

A Brief History of BI

In the early days, BI revolved around the following process:

  •      A business user would define a need, and submit a ticket to the IT department
  •      The IT department would gather the relevant data, often from data warehouses and cubes (Cognos, Business Objects, etc.), and deliver it to a business analyst
  •      The business analyst would then analyze the data using spreadsheets or some form of dashboards, and then create reports for the business user

Sounds like a cumbersome process, doesn’t it?

Even worse, it’s a very s-l-o-w process. A lag time of weeks or even months between the initial request and final delivery were common. Or perhaps I should say are common – many companies are still stuck in this “early days” process.

And data was often stale before it was even loaded into the data warehouses, since data was often collected from production databases on a weekly basis. So by the time business analysts finally got their hands on the reports, they weren’t exactly looking at up-to-date information.

Screen Shot 2015-01-14 at 3.07.27 PM

Eventually, companies like Tableau and Qlik (formerly QlikView) arose to fill the growing demand for visualization and dashboarding. Business analysts finally had the ability to slice and dice data to their own needs. That was great progress. But business users were still working with stale data.

But early on, BI processes revolved strictly around structured data. Data warehouses – 1990s technology – did not have the ability to capture unstructured data.

All data captures were from relational-based data storage. Only data that conformed to a conventional relational schema was captured; all other data was untouched.

Unstructured Data Gets Unlocked

Large companies like Yahoo and Google were crawling trillions of web pages, amassing massive amounts of data, and indexing the unstructured information for rapid searchability. They built Hadoop-like technologies to capture and analyze large volumes of unstructured data. And so the open-source technology Hadoop became quite popular for storing vast quantities of unstructured information – though not nearly as efficiently as structured data storage.

To facilitate the process of storing unstructured data, Hadoop created its own file system: HDFS (Hadoop Data File System). And Hadoop provided MapReduce technology, which allowed analytics to run on top of all that unstructured data.

The advent of Hadoop inspired companies to begin capturing ever-increasing quantities of unstructured data.

But the MapReduce technology has its flaws. It’s slow. It takes lots of time to run jobs that must sift through massive amounts of data. The time lag between asking a question and getting an answer can be substantial – and in many cases, entirely unacceptable.

Currently, many companies are using Hadoop to store huge quantities of unstructured data. And they’re combining the text data analytics with structured data analytics from data warehouses, and using applications such as Tableau to analyze the resulting amalgamation of data.

Traditional Business Intelligence solutions – based both on structured and unstructured data – have evolved to be of great value. They provide companies with a wealth of decision-making support that simply wasn’t available not so long ago.

But there’s a problem…

A Gap Between Capabilities and Needs

More and more, the business world is running on software. In many cases, software-based business models have even toppled long-entrenched business dynamos.

Netflix vs. Blockbuster is a classic example.

Netflix, enjoying the benefits and economies of operating a software-based business model, contributed greatly to putting Blockbuster and it’s huge empire of physical stores essentially out of business.

But as the business world becomes more software-oriented, companies increasingly need a way to gather insights into software operations. And traditional BI tools are failing companies in a very critical way. Software provides businesses flexibility to their operations. Code changes can easily alter how businesses are operating. The DevOps culture is resulting in multiple application updates per day, and BI tools and their huge latencies are simply not getting the job done.

Let’s Go Shopping

To illustrate the problem with traditional BI tools, let’s imagine that you’re logged-on to one of your favorite eCommerce websites to do some shopping – something that you likely do very frequently.

There’s a particular product you want to buy. But during the process, you’ll probably do some browsing around. Read some customer reviews. Consider alternatives.

And then once you’ve fulfilled your mission, and added your must-have item to your shopping cart, you’re likely to do some more browsing. Just some fun shopping. Some wish-listing.

Then, finally, you go through the checkout process and leave the site. The classic BI tool has only captured the end result of your interaction with the site – your purchase. What has the merchant company learned about you, their customer? Probably not as much as they could have or should have.

Opportunity Lost…

If the company is using only traditional BI tools, they’ve not learned nearly as much about you as opportunity offered. Sure, they’ve collected some data relating to your purchase.

But they could have learned so much more about you than what the mere transaction records offer.

They could have learned more about your interests. They could have learned how to serve you better. They could have learned ways to engage you far beyond your single purchase.

All invaluable data – and right there for the taking. But many companies don’t take it. Intentionally or not, many companies are turning up their noses at this unprecedented opportunity.

Opportunity Maximized…

Our Application Intelligence Platform offers companies a means of turning all of this disregarded or neglected data into golden opportunity. It provides:

  •      Real-time information about every interaction flowing through the software system
  •      Business context for every transaction type – logging transactions; add-to-cart transactions; checkout transactions; etc.
  •      End-to-end visibility of all transaction streams, front-end to back-end
  •      All information presented in a single dashboard

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Application Intelligence fills the gap that other BI tools ignore. As more companies adopt a software-defined model, customer experience becomes one of the most valuable commodities. Understanding your customer to give them a seamless experience is vital to long term success. With Application Intelligence, you can understand your customer better. It helps you to serve your customer better.

It helps to maximize the benefits of the hard-earned relationships you’ve established with your customers. And in the end, isn’t that what Business Intelligence is all about?

Start understanding your customer better and gaining insightful metrics. Try out AppDynamics for FREE today!