Embedded Analytics: Build or Buy
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A Guide to Making the Toughest Decision in Embedded Analytics Buy or build? This question has tormented IT and development teams since the beginning of commercial software. When it comes to embedding analytics into your application, there is a lot to consider. Does the convenience and quality of third-party commercial software outweigh the cost-savings and fine-tuned control of building embedded analytics on your own? In this webinar, we’ll lay out the pros and cons of both options and explain the trade offs of embedding third-party analytics software into your application versus building and embedding your own analytics. Review major considerations for embedded analytics Compare creating, embedding, and managing analytics in each scenario (buy and build) See live demonstrations of analytics embedded into a business application Join a live Q&A session with an embedded-analytics technical expert
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Embedded Analytics: Build or Buy
- 1. A guide to making the toughest decision in embedded analytics Embedded Analytics: Build or Buy?
- 2. 2 Hello from Jaspersoft! © Copyright 2000-2018 TIBCO Software Inc. Shane Swiderek Product Marketing Manager San Francisco, CA Scott Andersen Sr. Solutions Consultant Denver, CO
- 3. Data as a feature Winter Helping Users Reach Goals with Data Spring Embedded BI: All Things Considered Fall Modern Reporting At Scale Summer Building Data as a Feature Applications
- 4. 4 • Determining desired outcomes • Understanding requirements • Build vs buy comparisons • Live demos • Q & A Agenda © Copyright 2000-2018 TIBCO Software Inc.
- 5. 5© Copyright 2000-2018 TIBCO Software Inc. What are you trying to accomplish?
- 6. 6© Copyright 2000-2018 TIBCO Software Inc. Where / how do you intend to deploy?What is the desired level of integration / user experience? Who are your users? involve your users! How are you handling security and distribution of analytics?
- 7. 7 • Are they analysts? Technical? Business users? • What goals do they have? How could analytics help them with these? Determining desired outcomes © Copyright 2000-2018 TIBCO Software Inc. Who are your users? involve your users!
- 8. 8 • Cloud? • Public or private • On-prem? • Hybrid? • App servers? • Operating systems? Determining desired outcomes © Copyright 2000-2018 TIBCO Software Inc. Where / how do you intend to deploy?
- 9. 9 • Static reports (PDFs) that can be generated in your app • Reports/analytics tab or area within your app • Seamless integration – analytics mixed with operational parts of your app Determining desired outcomes © Copyright 2000-2018 TIBCO Software Inc. What is the desired level of integration / user experience?
- 10. 10 • Deploy single instance to multiple customers? • Dedicated instance per customer? • SaaS? • Application security and SSO? • Data security (row and column level) Determining desired outcomes © Copyright 2000-2018 TIBCO Software Inc. How are you handling security and distribution of analytics?
- 11. 11 • Determining desired outcomes • Understanding requirements • Build vs buy comparisons • Live demos • Q & A Agenda © Copyright 2000-2018 TIBCO Software Inc.
- 12. 12 • User experience • Level of integration? • Managing users themselves? (permissions to reports / dashboards) • Type of analytics (reports & dashboards vs self-service vs advanced self-service (discovery and beyond) Understanding requirements © Copyright 2000-2018 TIBCO Software Inc.
- 13. 13 • Data complexity • Access data from multiple systems? • What is the size of your data? • How do you plan to access it? • How fresh does your data need to be? Understanding requirements © Copyright 2000-2018 TIBCO Software Inc.
- 14. 14 • Environmental requirements • Multiple concurrent users • Multi-tenant deployment • Performance • Availability / scalability • Other environmental factors Understanding requirements © Copyright 2000-2018 TIBCO Software Inc.
- 15. 15 • Determining desired outcomes • Understanding requirements • Build vs buy comparisons • Live demos • Q & A Agenda © Copyright 2000-2018 TIBCO Software Inc.
- 16. 16 Why build? Control • Customize the functionality better • Customize look and feel better You’ve got the resources • You have enough developer resources with required skills © Copyright 2000-2018 TIBCO Software Inc. Cost of buying software • Software can be expensive
- 17. 17 Why buy? © Copyright 2000-2018 TIBCO Software Inc. BI not a core competency for most developers Give best-in-class BI functionality to your customers Building takes too long (you compete on time to market!) Support Focus your developers on building core product Scalability & high availability Security
- 18. 18 Build vs. Buy © Copyright 2000-2018 TIBCO Software Inc. Scalability / High availability Security (data and repository) Time to market Resources Design User experience Functionality
- 19. 19 Build vs. Buy © Copyright 2000-2018 TIBCO Software Inc. Scalability / High availability Security (data and repository) Time to market Resources Design User experience Functionality Build
- 20. 20 Build vs. Buy © Copyright 2000-2018 TIBCO Software Inc. Scalability / High availability Security (data and repository) Time to market Resources Design User experience Functionality Buy
- 21. 21 Build vs. Buy © Copyright 2000-2018 TIBCO Software Inc. Scalability / High availability Security (data and repository) Time to market Resources Design User experience Functionality Build / Buy
- 22. 22 • Determining desired outcomes • Understanding requirements • Build vs buy comparisons • Live demos • Q & A Agenda © Copyright 2000-2018 TIBCO Software Inc.
- 23. demo
- 24. 24© Copyright 2000-2018 TIBCO Software Inc. Where / how do you intend to deploy?What is the desired level of integration / user experience? How are you handling security and distribution of analytics? Who are your users? involve your users!
- 25. 25 • Determining desired outcomes • Understanding requirements • Build vs buy comparisons • Live demos • Q & A Agenda © Copyright 2000-2018 TIBCO Software Inc.
- 26. 26 What next? © Copyright 2000-2018 TIBCO Software Inc. See How to Get Started http://www.jaspersoft.com/getting-started Try Jaspersoft Free for 60 Days http://www.jaspersoft.com/download O’Reilly Books www.jaspersoft.com > Resources Get your question(s) answered by an expert Send questions to: na-jaspersoftdemo@tibco.com Next webinar: Special Jaspersoft Announcement! Key considerations for embedding Why embedding? May 15th May 16th
Editor's Notes
- Today we are going to be exploring a subject that just about every software team can relate to. That is weighing the options of building a particular component of your software product or service versus buying that component from an external software vendor. I’d like to address the elephant in the room. TIBCO is a software vendor and obviously our business, like any software business, revolves around selling the software we create. So you might be worried that we’re going to focus heavily today on trying to convince you that Buy is the best option. But you all are smart people and if buy is truly the best option for your scenario then you’re probably going to come to that realization at some point in your scoping process. So it’s actually in both of our interests to
- SHANE This webinar is part of the Spring theme, Embedded BI: All Things Considered. There is a lot to evaluate when looking to embed analytics into your applications. Throughout the course of this theme we are exploring all of the major considerations ranging from how to get started and choose the right type of analytics to how to embed them, to how to configure security and deploy analytics in multi-tenant SaaS applications. Each of the 4 themes throughout the year are actually sub-themes of a concept called Data as a feature. Data as a feature is about treating data as a core feature in your product or service and making data into a valuable asset to your users. This is a concept that we’ve collaborated on with O’Reilly Media and, if this sounds interesting to you, at the end of the webinar, I’ll point you to where you can learn about the concept further.
- But this is really a tricky subject. Whenever you’re integrating software into other software there’s a lot of think about. And what I think you’ll think find from today’s session is that it’s not really a build vs buy decision. It’s a build or buy to build situation. We’ll explore what I mean by that as we go through today’s content and look at
- The most important step before kicking off your project is answering this question. What are you trying to accomplish? What outcomes do you hope to achieve by embedding analytics into your application? Are you trying to reduce the amount of time you or your development team spends on fulfilling custom report requests for customers? Are you trying to make your application more competitive and more attractive to your users? Is there a time constraint involved? Is this project time sensitive? The answer to this question should be influencing your decisions at every point in this process.
- As you are determining desired outcomes for your embedded analytics project, there are four key areas to consider. Who are your users? Where do you intend to deploy? What does your application environment look like and what does it run on? What is the desired level of integration? This is correlated to what user experience you want to deliver. How are you handling security? This applies at the application level and the data level. We’ll get to that in more detail in a few slides.
- So step 1 is to identify who your users are, their skill levels and competencies. Are they data analysts? Do they have technical skills? Are they business users (operational workers or management) that perhaps don’t have either of these skills? If they are analysts, you can assume something about the type of analtyics you provide to them. They are likely going to want the ability to not just interact and consume analytics, but also create their own reports, dashboards, and analyses from the data you expose to them. If these are technical individuals, they may also want the interact with data and perform some level of analysis. In addition to that, there’s a chance they will be responsible for accessing data directly from the source system(s) and even building a metadata layer. The role of a metadata layer is to enables less technical people in the organization to more easily query the underlying data. This technical user is unique in that they might be both an administrator of analytics as well as an end-user. For business users, it’s critical that you are matching them with analytics that match their skill level. There are two reasons. One, there has been poor adoption of analytics by business users historically. Giving them analytics that are too complex is a sure fire way to continue that trend with your users. Two, even worse, if your business users are using the analytics you provide, and they don’t have the skill set, they’re probably going to come to the wrong conclusions. You’ll see in the green box in the upper right that we’ve emphasized the importance of involving your users. Take the time to understand who they are and what goals they have. Once you’re there, it will be much easier for you to determine what type of analytics they need and what experience you need to provide in order for them to reach their goals. Because business users don’t have the same technical or analyst background as other users, this group tends to be a prime candidate for embedded analytics where you can integrate analytics capabilities into the experience of applications they already use and are proficient at.
- The next step in the process of determining desired outcomes is to think about where and how you intend to deploy. Are you planning to embed in a cloud SaaS application? Is your application a single service or a set of smaller services? Would you want to deploy your analytics in its own container that is called and accessed by other containers when needed? Does your application run on particular application servers or operating systems? Reminding yourself of these specs will be particularly useful if you decide to embed third-party software into your application and need to make sure its compatible and won’t require a lot of custom configuration to get up and running.
- The third step is determining the desired level of integration. How deeply do you want to integrate analytics into your application? There are a few different methods for integrating. The most basic would be offering a way for users to generate a report in your app. Think of a financial statement or cell phone bill. These are static documents. Usually there is some form of a button in your app that users click to generate a report. The next level of integration would be embedding analytics using iFrames. This generally involves a user clicking on a reports or analytics tab in your app, and there they can engage with the analytics inside the iFrame. One thing to note with iFrames is that there are limitations to how much interactivity you configure between your application and what’s inside the frame. For example, it’s rather difficult to use components from your application to pass parameters into an iFrame and vice versa. Now, if your users don’t need that level of interactivity then iFrames could very well be sufficient. Again, this is why it’s so critical to understand your users. The last level is seamless integration. For web applications, this tends to be a pure javascript integration allowing you to turn analytics into a native component of your application. This level opens up a whole slew of possibilities for configuring an experience in your app that makes it particularly easy for non-technical, non-analyst business users to be effective with data. Scott will expand on this later and show you in his live demos what this sort of experience can look like.
- The final outcome to consider before we move onto the next section is how are handling security currently and how will that interface with what you’ll need to distribute analytics securely in your app. This step is not sexy but perhaps the most important of them all. Will you deploy a single instance of your software to each customer? That would solve a lot of your security concerns but it could also be much more expensive depending on how many customers you have. If you are deploying to many customers, you might have some sort of multi-tenant deployment. This is more difficult to configure but can mean significant costs savings and also give you a way to manage all of your customers and their data from a centralized location and also roll out and distribute updates in a much easier way. For SaaS applications, multi-tenant deployments are especially popular for those reasons. You need to think about security at the application level. Most likely you’re not going to want to have your users login to your application and then have to relogin to your embedded analytics capabilities. This is another one of those concerns that would apply moreso to the buy scenario. Lastly, data-level security. You are probably providing analytics to different types of users, that need different levels of access to data. You can control data access at the row and column level. How important is that to you is up to you to determine.
- Now that we’ve seen the desired outcomes for embedded analytics. We’re going to take a brief look at the requirements to make that reality. After this, I’m going to hand you over the Scott who will cover the build vs buy comparisons and then dive into the live demos.
- For requirements around user experience. Again, you are going to want to start with your desired outcome for level of integration. Requirements are going to vary based on level. Embedding PDFs or static reports are going to require some sort of RESTful call to your database to access and generate the report. Embedding iFrames are relatively simple. You are just taking the URL of the analytics (which would be located in some sort of server) and plugging that into the iFrame to render the reports, dashboards, or self-service capabilities. Seamless integration will require you to write javascript to natively integrate interactive data visualizations into your applications. You’ll also want to have the ability to manage users themselves. I touched on this in the data security point a few slides back. Again you will need to have a system in place that can assign roles, attributes, and other identifying characteristics to users that can then be used to determine their level of access to analytics. Lastly, type of analytics is going to be largely dependent on the skill levels of your users. Make sure that you are not making the mistaking of assuming your users are more proficient with data than they are.
- Second, and this is a big one, is data complexity. Are you pulling data from multiple systems for your analytics. What is the size and planned attack for accessing data. Do you need to do reporting or analysis from a data warehouse type object, do you want to virtualize data across systems and connect to it live, do you want to direclty connect to some large Hadoop data store. Last, how fresh does your data need to be? Do your users need to see data in real-time. Is it sufficient from data to be updated on intervals of 10 min 1 hour or more? These are key requirements that you need to think about and Scott will show you in a few slides on how these contrast for build vs buy scenarios.
- The final slide before I hand control over to Soctt is around Environmental requirements. This applies to workload and, as you can imagine, there are ton of variables involved in this. Some things to think about are how many concurrent users do you expect to have? Will the deployment be multi-tenant How will performance be affected by how you have your data orchestracted? How available is your data? Is your enviorment prepared to scale to peak demand? And there are a number of
- SHANE handover to SCOTT
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- SHANE
- SCOTT Fresh delivery demonstrating different types of analytics (report, dashboard, ad hoc) and levels of integration (iframe vs visualize.js) for visualize.js, expose embed code and explain the simplicity of making analytics an integrated component of your application JRS quick peek at configuring multi-tenancy explain domains and importance of a metadata layer if self-service is a requirement
- SHANE Whether you are building or buying, these are the things you need to think about when embedding analytics.
- SHANE