Free Guide to Business Intelligence Software (2013) by think businessy


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A free guide to Business Intelligence software by Think Businessy that summarizes everything you need to know and were afraid to ask about what business intelligence software is, why it's useful and what capabilities it can offer your business.

There are many makes and types of business intelligence software product available to buyers these days.

Which type of product is right for your business? In this guide I provide a perspective on the capabilities you might be unknowingly looking for – just to make sure everything is ‘in the box’.
Topics covered include:
• What is Business Intelligence?
• The Players
• Capabilities
• Constructs
• Technology Disciplines
• Future Trends
• Check-list
• Final Thoughts

Within this guide I haven’t spent too much time profiling each of the products as this isn’t particularly helpful given that specifications and features change all of the time so it is always a good idea to conduct your own web research. I do however provide a summary of the more popular products at the end of the article.

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Free Guide to Business Intelligence Software (2013) by think businessy

  1. 1. 1 The Business Intelligence Software Guide 2013 ThinkBusinessy 8th August 2013 Ian Tomlin
  2. 2. 2 Introduction There are many makes and types of business intelligence software product available to buyers these days. Which type of product is right for your business? In this guide I provide a perspective on the capabilities you might be unknowingly looking for – just to make sure everything is ‘in the box’. Topics I cover include:  What is Business Intelligence?  The Players  Capabilities  Constructs  Technology Disciplines  Future Trends  Check-list  Final Thoughts Within this guide I haven’t spent too much time profiling each of the products as this isn’t particularly helpful given that specifications and features change all of the time so it is always a good idea to conduct your own web research. I do however provide a summary of the more popular products at the end of the article.
  3. 3. 3 What is Business Intelligence? While there are many definitions the role of business intelligence software is to source insights from data. There are two main forms of data:  Structured data – The sort of stuff you see in a database or a CSV (Comma Separated Value) file that you’d expect to open in a desktop spreadsheet application. These days we also have formats like XML that are essentially structured composite files that carry data and a description of the data (so the data file might say, “I’m an invoice” and “This first column is the Invoice Number” which helps with data transfer between computer applications).  Unstructured data – Data that’s held in documents and other formats that hasn’t already been placed into nicely labelled boxes but we still might want to mine it. The technology tooling required to surface useful data, organize it and present it is complex and embraces a variety of capabilities, constructs and technology disciplines. Few Business Intelligence tools cover all of the areas - but that’s okay because you don’t always need every attribute. The Players With so many vendors in the business intelligence market it would be a pretty meaningless and unfruitful exercise as the boundaries of capabilities for each vendor are constantly in a state of flux. Even segmenting business intelligence tools into ‘pre-cloud’ or ‘Made of the cloud’ does not provide great signage to buyers given that many of the old school vendors have acquired or developed in-memory and web 2.0 self service style capabilities. Some of the more notable names in BI with exceptional technology or big brands include SAS, IBM, MicroStrategy, SAP BusinessObjects, Oracle Hyperion, Informationbuilders, Microsoft, Tibco, Qliktech, Tableau, Actuate, Encanvas, Targit, Pentaho, Yellowfin, Birst, iDashboards, Jedox, Borad International and Jaspersoft. In addition to these software providers there are literally hundreds if not thousands of business intelligence consulting and IT services companies around the world that offer expert skills in selection, deployment and outsourcing of BI services where a ‘blended’ strategy is adopted. The best advice therefore is to define the requirements before attempting to select the tool-ware and service provisioning.
  4. 4. 4 Capabilities Capabilities are big categories of ‘things’ that business intelligence DOES – not be confused by HOW it gets done. Business Intelligence has four main areas: Enterprise Performance Management A business intelligence platform for managing organizational performance including governance of progress towards strategic objectives as defined in a scorecard and the monitoring of daily activities that result in budgets and forecasts being achieved. Business Intelligence software used for this purpose will often adopt the very popular Balanced Scorecard model to frame and articulate strategy as exampled in the Strategy Map illustration above. Daily Operating Controls and Operational Reporting Applications used to disseminate reports that show progress towards budget and forecast targets so that managers can react to sub-optimal performance and before it’s too late to do anything about it.
  5. 5. 5 Operational Analytics Applications used to source actionable insights that cause managers to review their processes and decisions in search of improvements. Community/Social Business Intelligence Applications used to source insights within a community to aid community learning and cooperation; often resulting in the creation of new or enhanced applications and processes adopted by the community.
  6. 6. 6 Constructs I use the term construct to describe core characteristics of HOW business intelligence software does what it does. These are: 1. Capture – In many analytical applications there is more data to be added. Tools to author forms are important to enable keyboard data entry from PC, tablet and mobile phone devices. 2. Discover and harvest – The ability to harvest data from multiple sources is essential for most data analysis applications. Advanced platforms provide opportunities for discovery of new insights held within data. For example, natural language search tools can present data on companies that are similar to those in the enquiry to suggest content that may be interesting to the enquirer. 3. Assimilate – Assimilation is an essential yet least understood aspect of business intelligence and operational analytics software. Assimilation is about get data brought into a useful form for analysis. The extent to which assimilation is required will depend on where the data is held, what form it is in, and how it needs to be used. This stage might include tools that normalize data, sort it, cleanse it and mash-it into a form that’s useful. 4. Analyze and interpret – Making sense of data has always been a feature of business intelligence tools since the humble spreadsheet came of age. Analytics is a challenging aspect for vendors because users have such varied requirements and expectations. Interpretation is ‘in the eye of the beholder’ which is why self- service tools have become such a competitive battleground. 5. Present– The presentation of data could be anything from a simple table to sophisticated charts, maps and data visualizations. Data becomes generally more interesting when people can look at two, three or four characteristics of the subject on the same page (examining customer data that includes spending habits, social networking behavior, location and affluence can expose new understanding of customer personas that would be difficult to find if each attribute were explored separately). Presentation needs to cater for analysis of single or multiple attributes of one entity, or single or multiple attributes of multiple entities and should include:  Tables with the ability to sort, group, order and compare  Simple (easily absorbed) entity analysis views like gauges, traffic lights, slider scales and ‘direction of trend’ arrows that bring at-a-glance understanding  Enlightening charting and graphing tools including bar charts, pie charts, line graphs, geo-spatial maps, spatial graphs, spider diagrams etc.
  7. 7. 7  Scorecards – that enable formation and comparison of key performance indicators in a dashboard to accommodate for period by period analysis, mixed compositions of KPIs including run-rate, first-past-the-post etc. These days it’s hard to imagine any of the above presentation modes without the ability to drill-down into source data and download data for further analysis. Drill- down features are so important to aid comprehension and to enable the enquirer to gain a deep understanding of ‘the data behind charts and graphs’, and how summary values have been aggregated. 6. Manage enquiries and socialize – It can become time consuming for users to keep re-building the reports and report-views of data that are most useful. Expect BI platforms to therefore provide the means for users to personalize their own suite of queries. Establishing profile-based customized report selections means that users don’t have to keep re-creating the same enquiries time and again. In the noughties, users expect to be able to socialize their reports and charts; normally by publishing them to a dedicated webpage so they can share the precise report view they’re looking at with colleagues. 7. Predict – Business Intelligence software becomes REALLY INTERESTING to buyers when it can not only expose insights but predict consequences on growth opportunities, resources, operating constraints and exposure to risk or unbudgeted costs. It takes a heady mix of clever software AND a deep appreciation of how processes work to create the magic formula needed to source predictive analytics. 8. Install new or adapted processes – There’s little point learning if you can’t do anything about it. Increasingly, Business Intelligence platforms are providing the tooling to enable business analysts to apply learning lessons. Modern BI platforms install changes to operating processes by providing the methods and tools to design and deploy new applications or adapting existing ones. Tools like Encanvas and Interneer enable cross-platform, cross-discipline workflows to be installed that run across existing administrative systems and silos of data.
  8. 8. 8 Technology Disciplines I use the term ‘technology discipline’ to describe the big chunks of technology found in Business Intelligence applications. The market for tools is so diverse these days that it’s difficult for buyers to compare like-for-like capabilities. Many vendors have particular strengths, or specialize in a specific discipline which means creating a solution can be a choice between:  Purchasing a ‘total platform solution’ from a software vendor where everything is expected to be sourced by one vendor including the expertise to deliver outcomes.  Purchasing a ‘pick and mix’ of best of breed software vendor tools and building your own solution.  Inviting a third party IT Services company to take on the project overhead of managing business intelligence sourcing across your enterprise based on an agreed set of outcomes. Here I describe the most prevalent technology disciplines under the headings of the constructs I’ve outlined in the previous section. Note that I’ve not produced a fully comprehensive list as it might stretch into pages! Neither have I documented ‘IT hygiene’ factors such as User permissions management, security, scaling, portal deployment, cross-browser compatibility and mobile integration (etc.) that are ‘must-have’ business computing requirements. (Capture)  Key-fill forms applications - To enable keyboard-fill data entry of data that adds-to existing business insights applications. Applications normally need to support one-to-many and many-to-many data relationships and support cross-browser deployment to PC, tablet and mobile devices. (Discover and harvest)  Natural language search engines – To spider the Internet and recover content held in unstructured content (documents and websites articles) based on natural language terms.  Recommendation engines – To source recommendations of contextualized insights (view services like Factiva and you will see that search enquiries on a topic such as the name of a company will result in other similar companies being ‘recommended’ to the enquirer. You will also see similar side-bar discoverable insights from searches on popular mapping tools like Googlemaps).  Data source connectors – To connect to data sources and file formats. These generally take the form of a wizard that makes it easy to connect to a data source and configure an extraction of data or two-way dynamic
  9. 9. 9 integration. Vendors like Microsoft, Tibco, Encanvas, Xchanging, Pentaho, and Mulesoft all offer suites of data connectors and integration tools so you can source virtually any data from any source. (Assimilate)  Information upload and flow management tools – To automate triggering and extract workflows for the purposes of loading data from its various sources into the business intelligence environment (see products like Information Flow Designer from Encanvas).  Extract, Transform and Load tools – To source data and make it usable in business intelligence applications; normally by executing transforms.  Data mashup tools- To bring data together in news ways by picking ‘bits’ of data from different places and creating new data structures with it (for example, taking data from a spreadsheet and combining it with data from Oracle and SAP in the same table-view). (Analyze and interpret)  Tables with Sorting, Ordering, Filtering and Grouping – To offer users the ability to interrogate data using interactive table views.  Comparison Views – To offer users the ability to compare entities side-by- side in table views.  Metering and Charting with Drill-down – To offer users the ability to view data in the form of meters and charts used to report on aggregated data views with the ability to drill-down to the original data; probably in an interactive tabular view. (Present/Self-service tooling)  KPI Scorecarding – To enable users to create scorecards by specifying a series of key performance indicators each with its own formative logic – such as first-past-the-post, run-rate, period comparison etc.  Graphing and Charting – To enable users to create charts and graphs from the assimilated data without complexity or programming.  Mapping and Visualizing – To enable users to geo-map or visualize data using spatial graphing tools. (Manage enquiries and socialize)  Web page/dedicated-URL sharing – To enable users to share their insights by using dedicated-URLs that can be pasted into messages etc.  Interactive slider and choice controls – To enable users to interact with data in real-time to understand likely impacts of decisions.  Voting and crowdsourcing – To enable communities to contribute opinions on the analytics being shared.
  10. 10. 10 (Predict)  Prediction engines - To predict pinch-points in areas of resourcing capacity, process loadings, consequences of decisions etc. (Install new or adapted processes)  Applications design tools – To create applications that facilitate the iteration of business processes that are demanded when users seek to apply the learning lessons surfaced by actionable insights.  Business Process Management (BPM) workflow automation – To install cross- cutting workflows that run across silos of business operation in support of the change agenda demanded when users seek to apply the learning lessons surfaced by actionable insights.
  11. 11. 11 Future Trends The future trends emerging in Business Intelligence include: 1. More ‘born of the cloud’ BI products It would be hard to imagine a business intelligence vendor surviving if they aren’t able to provide a cloud delivered service. Companies like Encanvas and Tableau have mature and sophisticated cloud offerings that make it painless to configure a private-cloud environment within which company data can be assimilated without risk of security breaches. In the architectural purity debate, platforms that are able to deliver their insights through a browser agnostic front-end will inevitably be favored against those that require plug- ins or downloads. It still amazes me how incredibly poor companies like IBM and Microsoft are at supporting the diverse range of browsers out there. It seems these bigger players are confident enough in their brand positions to say to customers ‘You can have IE and Safari if you’re lucky’ which a decade ago was possibly good enough. If it was then, it isn’t anymore. The products that will eventually grow to become the leaders in this industry will have been ‘born’ in the cloud and of cloud technologies. Many of the current products are built on code authored in the 1990’s and that’s a big problem. Technologies like in-memory processing and use of AJAX tools CAN be bolted on to legacy platforms but eventually the complexity and cost of supporting aging technology platforms becomes a competitive Achilles’ heel. 2. Greater focus on sourcing of actionable insights than technology tools Whilst dashboards and charts are the ‘bread and butter’ of business intelligence solutions, what business people expect now are ACTIONABLE insights that cause them to take action. The company that is leading the charge to prove how effective and influential operational analytics can be to bolster business success isn’t actually a business intelligence company at all. It’s Google. Take a look at Google Analytics and you see a demonstration of the art of operational analytics done well. Now imagine having Google Analytics across every aspect of your business landscape. Wow. Buyers are worried far less about tools than they ever used to be. They are far more interested in outcomes. It’s the actionable insights, not the operational analytical tools that deliver them, that’s taking center stage. 3. Increased embedding of BI tooling into business apps Google Analytics also demonstrates the power of incorporating business intelligence technologies into the operational platforms that business people use. No longer is business intelligence software something separate, it is
  12. 12. 12 embedded into the applications people produce. In this sense the clever tools of business intelligence software becomes smaller parts of a bigger system. One could argue that platforms like IBM WebSphere and Microsoft SharePoint have been doing this for some time. Take a look at Oracle’s fusion apps and you will see the very best of operational analytics technology ‘ready-for-use’ and built within the core applications companies can now purchase on a cloud. Business intelligence offerings like Tibco Spotfire and Encanvas BusinessIntel take on the shape of applications design tool-kits that bolt into existing applications and become as one with them. Meanwhile database platforms like SAP Hana are symptomatic of the trend to merge operational and business intelligence data management structures into one. This reduces the complexity of IT architectures and increases the possibility of creating a ‘single-version-of-the-truth’. 4. More focus on predictive technologies What tends to happen when people use business intelligence (when it works well) is they start to see in dashboards and activities patterns of ‘things that happen’ they can act on. Over time it becomes apparent that the task of seeking out these insights is itself time consuming and it would be better if the SYSTEM could itself predict these occurrences and recommend actions. The ability to ‘predict’ resource constraints, understand events that could create opportunity and risk – and other stuff – becomes smarter and more effective over time. The rewards can be enormous. 5. Platforms that cover ALL of the bases As I outlined earlier, modern business intelligence software has to cover ALL of the capability areas including capture, discovery and harvesting, assimilation, analytics and interpretation, presentation, socialization and enquiry, prediction and solutions delivery. At present only a minority of vendors are able to service all of these bases and often they achieve this only through use of third party apps. Progressively as the market matures and it becomes more of a brand war than a feature by feature battle, we can expect that all of the major vendors will have to find ways to offer COMPLETE solutions; either through development or acquisition. 6. Cloud BI going main-stream Business intelligence software has to-date been seen as the cherry on the cake; something businesses purchased later when they realized the system of record they’d purchased didn’t actually source the performance analytics and actionable insights they required. In future, business applications that DON’T offer rich analytics and self-service tooling to source actionable insights simply won’t be purchased. The Software-as-a-Service (SaaS) model enables
  13. 13. 13 buyers to choose their products in full view of their strengths and weaknesses. Vendors are no longer able to hide behind the PowerPoint sales pitch or well- fashioned demo site. The ‘capabilities’ of business intelligence software will eventually merge into the Social Operating Systems that people use in their work-day and as users we will see these as features of the tools we use rather than seeing them as something different. 7. (And finally…) Price erosion Google said almost a decade ago that buyers could one day expect to get ‘all the software they needed’ for $10 a head. I still believe this is ultimately the way the industry will go and it becomes all the more possible when vendors like Amazon, Apple, Encanvas, Microsoft, IBM, Oracle, SAP, and others continue to mature their Social Operating Systems platforms in the cloud and start to provide menu-based industry and process specific solutions that buyers can buy with ‘good practice’ built-in. Checklist for Buying Business Intelligence Software Requirements vary so much for business intelligence that no single vendor offerings will always be the best-fit. Here’s a simple check-list? 1. Qualify the role that you expect business intelligence to play in your business and the BI capabilities you will need. Some businesses (and indeed business models) don’t change that frequently in which case a more traditional business intelligence platform will probably work, but if you expect users to demand intuitive self-service tools and expect your dashboards and operational analytics to grow and grow then one of the more ‘agile’ platforms would spring to mind. Depending on your industry there may be vendors that have ‘ready-to-deploy’ solutions to match your immediate role needs and bring faster ‘time-to-value’. 2. Consider where the data your business intelligence platform will need to harvest is held and in what form – it could be coming from desktop apps, existing administrative systems, documents, web services, third party services etc. – and check to see if the BI tools you’re considering can access them. Check for data connectors and assimilation capabilities. 3. Audit the ‘constructs’ you will require and make sure your BI tools have the ability to service these requirements – either from one vendor, or from several. 4. Review the ‘hygiene’ issues like federated user permissions management, security, scalability, cross-browser support, multi-threading capabilities and enquiry processing potential.
  14. 14. 14 Final Thoughts While not all BI offerings are the same but innovation in the Business Intelligence market does seem to be reaching its peak. While some players have fallen off of the pace, the majority are able to offer ‘complete’ solutions one way or another; even if it involves integration with third party tools or months of development! Competitive differentiation is strongest in areas of:  Real-time analytics – making sense of data while it’s still moving!  Self-serviceability tooling – giving users the tools to serve themselves with new analytics, new applications etc.  Discovery (exposing new insights from queries you haven’t even thought of)  Assimilation tooling such as data mashing and normalization  Time-to-value (often achieved by off-the-shelf process or industry specific dashboards and reports)  Predictive analytics that reduces manual interventions Faced with maturing technology, we appear to be entering a new period where BRAND will play an ever increasing role in decision making. This is good news for companies like SAP, IBM, Oracle and Microsoft – and potentially for Apple, Nokia, Amazon and Samsung – that already have BIG brands, particularly as business intelligence tooling becomes integral to business applications. We have seen in the past 20+ years a move towards ‘platforms’ in business computing where companies sacrifice any opportunity for competitive advantage through the tools they use for ‘good practice processes and a single view of data brought about by the ambition of a single computing system. This norm of behavior in buying approaches adopted by large corporations has really helped the larger brands to dominate. Nevertheless, it’s not all bad news for new entrants and smaller players that may be light on brand awareness but have the more adaptive ‘born of the cloud’ tools buyers need and the opportunity to grow their brand story thanks to the new playing field that the cloud offers. When it comes to surfacing actionable insights and harvesting the BIG DATA that’s becoming available to business users around the world, there’s still plenty of room for innovation.
  15. 15. 15 About the Author Ian Tomlin is a researcher, writer and author on topics of customer science, organization design and agility, stretch strategy and enterprise technology. He has worked in the European Information Technology sector since 1990 holding sales and marketing management roles covering disciplines including business intelligence, document management, computer printing, output management, document, content and knowledge management, search, cloud computing, enterprise social networking, enterprise integration, ETL and data mashups. Article Sponsors Workforce and Talent IT and Technology Data Engineering and Customer Science Books by Ian Tomlin Agilization – The regeneration of competitiveness (2008) Cloud Coffee House – The birth of cloud social networking and death of the old world corporation (2009) SOS - Social Operation Systems (2011) Blogs and Articles by Ian Tomlin Loyalty Beyond Reason – @ictomo ThinkBusinessy – @ThinkBusinessy Slideshare -