Taming Big Data with Visual Analytics

Taming Big Data with Visual Analytics
Corvelle Consulting 4/19/2017 Taming Big Data with Visual Analytics Taming Big Data with Visual Analytics My name is Yogi Schulz Thank you to CIPS executive for inviting me to speak today Many companies are trying to determine how to drive value from Big Data and Visual Analytics to advance their business plan Today I’ll describe Big Data and Visual Analytics My goal is to show how Visual Analytics can tame Big Data Sometimes the buzzword density of IT presentations is a little high I’ve tried to continue that tradition today by weaving two buzzword phrases together This presentation is based on the experience I gathered from a project I led for an oil & gas producer in 2013 The project is continuing into 2014 because we were able to build confidence in the project sponsor in 2013 that we were on the right track. Confidence was achieved by: Selecting an appropriate Visual Analytics software package Implementing the software smoothly and on time Training the end-users, production engineers in our case, thoroughly Delivering some modest but irrefutable, tangible benefits in the first year Staying focused on the business case and not becoming distracted by interesting, adjacent problems and solutions Taming Big Data with Visual Analytics

Yogi Schulz Biography Partner in Corvelle Consulting
4/19/2017 Yogi Schulz Biography Partner in Corvelle Consulting Information technology related management consulting Microsoft Canada columnist & CBC Radio guest PPDM Association board member Industry presenter: Project World - 6 years PMI – SAC - 3 years PMI - Information Systems SIG - 2 years PPDM Association - several years Title: Yogi Schulz - Biography Who am I? I’m a Partner of Corvelle Consulting We offer information technology related management consulting We have executed many project management and systems development assignments for our clients Many of our clients operate in the upstream oil & gas industry I have written many columns for Computing Canada. These columns have tended to focus on project management and systems development themes. The audience is composed largely of IT executives and managers For two years, I wrote columns for the Microsoft website. These columns described useful responses to IT developments for a general audience of business managers For a while I was a CBC Radio guest with an information technology theme I’ve participated in many industry conferences as a presenter: Project World - 6 years PMI SAC – 3 years PMI - Information Systems SIG – 2 years Professional Petroleum Data Management Association - PPDM Association - several years Taming Big Data with Visual Analytics

Presentation Outline Presentation objectives Big data Definition
Corvelle Consulting 4/19/2017 Presentation Outline Presentation objectives Big data Visual analytics Conclusions Recommendations Questions & Answers Definition Trends Value Here’s the outline of my presentation today: Big data and visual analytics are about managing and deriving business value from the growing mass of data most of our companies are gathering Presentation Objectives First, I want to lay out a few objectives for the time we have together here today Big data Then we’ll discuss what big data is and where it’s headed Visual analytics Then we’ll consider what visual analytics is and how we can go about delivering value using this software Conclusions We’ll wrap up with some conclusions and recommendations Recommendations Questions & Answers I invite you to interrupt at any time with a question Just don’t throw anything If I can provide a short answer, it’s better to answer the question immediately because the answer tends to be useful to everyone If the answer feels longer, then I’ll defer it to the end of the presentation Some in the oil & gas industry may long for a return to the idyllic calm of the past If any of you have this nostalgic view of the oil & gas industry; forget about it The future will bring more changes and upheaval than the recent past; big data and visual analytics are part of the change and upheaval Definition Trends Value Software Taming Big Data with Visual Analytics

Presentation Objectives
Corvelle Consulting 4/19/2017 Presentation Objectives Presentation Objectives Here’s what I want us to achieve today Increase our understanding of big data What is big data? Focus in particular on the issues of accessibility, performance and management Increase our understanding of the value of visual analytics What is the incremental benefit that visual analytics brings to the opportunity to wring more value from our data? Here’s an oil & gas example of using visual analytics to better understand production variance This screen shot is taken from the VISAGE visual analytics software package You’ll immediately see that the data is presented in a clear and understandable way What’s not obvious in this image is that all the graphic elements are clickable to drill into the data: To narrow down on the source of the problem variance Or to present the data on another chart for a different view Increase our understanding of big data Increase our understanding of the value of visual analytics Taming Big Data with Visual Analytics

Big Data Big Data What is big data?
Corvelle Consulting 4/19/2017 Big Data What is big data? As it’s name suggests, big data refers to the mountain of data that our companies are now collecting It’s feasible to collect lots of data because the cost of collecting, storing and managing that data is now acceptable Only a few years ago this cost was horrendous and therefore data was collected much less The issue is that big data is turning into an avalanche that is creating lots of data management problems for our companies Big Data Taming Big Data with Visual Analytics

Pointy-hair Boss Explains Big Data
Corvelle Consulting 4/19/2017 Pointy-hair Boss Explains Big Data Pointy-hair Boss Explains Big Data Source: D2012_07_29.gif As usual the Pointy-hair Boss gets it horribly wrong Consultants say three quintillion bytes of data are created every day. Consultants are not saying that Who knows how much data 3 quintillion bytes of data are? I sure don’t It comes from everywhere. It knows all. The data does not know all Deriving value from the avalanche of data is what the challenge and opportunity of visual analytics is all about According to the Book of Wikipedia, its name is “Big Data”. This description of Big Data is definitely not found in Wikipedia Taming Big Data with Visual Analytics

Corvelle Consulting 4/19/2017 Big Data Definition “Big data” is high-volume, -velocity and -variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making Gartner’s big data definition “Big data” is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making As far back as 2001, industry analyst Doug Laney (currently with Gartner) articulated the now mainstream definition of big data as the three Vs: volume, velocity and variety1. 1 Source: META Group. "3D Data Management: Controlling Data Volume, Velocity, and Variety." February 2001. Taming Big Data with Visual Analytics

Big Data Defined Data Velocity Data Volume Data Variety
Corvelle Consulting 4/19/2017 Big Data Defined Data Velocity Big Data Defined I like how this graphic illustrates the definition I just read to you Data Volume. Many factors contribute to the increase in data volume. Transaction-based data stored through the years Increasing amounts of sensor and machine-to-machine data being collected. In the past, excessive data volume was a storage issue. But with decreasing storage costs, other issues emerge, including how to determine relevance within large data volumes and how to use analytics to create value from relevant data. Unstructured data streaming in from social media Data Velocity Data is streaming in at unprecedented speed and must be dealt with in a timely manner. RFID tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time Reacting quickly enough to deal with data velocity is a challenge for most organizations. Data Variety Data today comes in all types of formats Structured, numeric data in traditional databases such as financial transactions Information created from line-of-business applications Unstructured text documents, , video, audio, stock ticker data Managing, merging and governing different varieties of data is something many organizations still grapple with. At SAS, we consider two additional dimensions when thinking about big data: Variability. In addition to the increasing velocities and varieties of data, data flows can be highly inconsistent with periodic peaks. Is something trending in social media? Daily, seasonal and event-triggered peak data loads can be challenging to manage. Even more so with unstructured data involved. Complexity. Today's data comes from multiple sources. And it is still an undertaking to link, match, cleanse and transform data across systems. However, it is necessary to connect and correlate relationships, hierarchies and multiple data linkages or your data can quickly spiral out of control. Other researchers and thought leaders have added the dimension of Data Value to this definition The point is that managing and analyzing tons of data is a useless exercise if some economic value can’t be derived from this work Data Volume Data Variety Taming Big Data with Visual Analytics

Digital Storage in Place
Corvelle Consulting 4/19/2017 Digital Storage in Place Digital Storage in Place Data volumes are growing no matter how you measure it The Digital Universe in 2020: Big Data, Bigger Digital Shadows, and Biggest Growth in the Far East December 2012 How many of you are struggling to cope with the growing volumes of data? Are there any approaches that are helping? More sophisticated management Archiving Deduplication Using Cloud services Outsourcing data management Exabytes Taming Big Data with Visual Analytics

Storage Cost Trends Storage Cost Trends
Corvelle Consulting 4/19/2017 Storage Cost Trends Storage Cost Trends While the cost per gigabyte of disk storage continues to plummet, this raw hardware unit cost is being overwhelmed by the total gigabytes in use, the environmental cost and the management cost for people and software These are the major cost components of total cost of ownership or TCO and they are growing Which cost components are giving you heartburn? Taming Big Data with Visual Analytics

Big Data Skills in Demand
Corvelle Consulting 4/19/2017 Big Data Skills in Demand Big Data Skills in Demand You can tell that big data is a big trend when some employers resort to billboards to recruit talent Are you able to attract and retain the staff with the expertise that you need? Taming Big Data with Visual Analytics

Big Data Issues Technology People Processes
Corvelle Consulting 4/19/2017 Big Data Issues Technology Multiple incompatible data silos Inadequate development and management tools People Shortage of data scientists Lack of communication between data scientists and business users Processes Insufficient attention to data quality Big Data Issues On this slide, I’ve shown the 3 biggest problems that we’ll need to at least partially address in big data to achieve value for our companies The 3 big problems in big data (hint: They all involve people) Technology Multiple incompatible data silos Inadequate development and management tools People Shortage of data scientists Lack of communication between data scientists and business users Processes Insufficient attention to data quality Which of these issues are you wrestling with? Are there some strategies that you’re pursuing that you could share with us? We’re at risk of being overwhelmed by big data or crashing in our efforts to tame it Taming Big Data with Visual Analytics

Value of Big Data Making data openly available
Corvelle Consulting 4/19/2017 Value of Big Data Making data openly available Supporting experimental analysis Assisting in defining market segmentation Supporting real-time analysis and decisions Facilitating computer-assisted innovation Value of Big Data Big data is all about facilitating or enabling other business processes Big data is not an end in itself The value of Big Data comes through Analysis and the application of the results to specific business needs Making data openly available Creating transparency by making big data easily and widely available for business and functional analysis to achieve higher quality, lower costs, reduce time to market Supporting experimental analysis Supporting experimental analysis in individual locations that can test decisions or approaches, such as specific market programs Assisting in defining market segmentation Assisting, based on customer information, in defining market segmentation at more narrow levels Supporting real-time analysis and decisions Supporting real-time analysis and decisions based on sophisticated analytics applied to data sets from customers and embedded sensors Facilitating computer-assisted innovation Facilitating computer-assisted innovation in products based on embedded product sensors indicating customer responses Notice how these value statements are all about enabling the business Here’s one analyst's estimate of the contribution that big data has made to business improvements in various industries What value have you found in the big data you’ve accumulated in your business? Taming Big Data with Visual Analytics

Big Data Market Forecast
Corvelle Consulting 4/19/2017 Big Data Market Forecast Wikibon Sizes the Big Data Market Essentially this graph says that vendor revenue for big data related hardware, software and services will grow seven fold between 2011 and 2017 Wikibon includes the following products and services under the umbrella of Big Data: Hadoop software and related hardware NoSQL database software and related hardware Next-generation data warehouses/analytic database software and related hardware Non-Hadoop Big Data platforms, software, and related hardware In-memory – both DRAM and flash – databases as applied to Big Data workloads Data integration and data quality platforms and tools as applied to Big Data deployments Advanced analytics and data science platforms and tools Application development platforms and tools as applied to Big Data use cases Business intelligence and data visualization platforms and tools as applied to Big Data use cases Analytic and transactional applications as applied to Big Data use cases Big Data support, training, and professional services Taming Big Data with Visual Analytics

Visual Analytics Visual Analytics
Corvelle Consulting 4/19/2017 Visual Analytics Visual Analytics Let’s turn now to the other half of the presentation How does Visual Analytics actually tame big data? Taming Big Data with Visual Analytics

Visual Analytics Definition
Corvelle Consulting 4/19/2017 Visual Analytics Definition Visual analytics combines automated analysis techniques with interactive visualizations to enable: Effective understanding Reproducible reasoning Defensible decision-making in the context of large and complex data sets Visual Analytics Definition Visual analytics is more than just visualization Visual analytics is an integral approach to decision-making that combines visualization, human factors and data analysis Visual analytics combines automated analysis techniques with interactive visualizations to enable: Effective understanding Reproducible reasoning Defensible decision-making in the context of large and complex data sets Taming Big Data with Visual Analytics

Corvelle Consulting 4/19/2017 Visual Analytics Goal Synthesize information and derive insight from massive, dynamic, ambiguous, and often conflicting data Detect the expected and discover the unexpected Provide timely, defensible, and understandable assessments Communicate assessments effectively for action Visual Analytics Goal The goal of visual analytics is the creation of tools and techniques to enable people to: Synthesize information and derive insight from massive, dynamic, ambiguous, and often conflicting data Detect the expected and discover the unexpected Provide timely, defensible, and understandable assessments Communicate assessments effectively for action Another way to state the goal is that finding actionable patterns and relationships in torrents of numbers or endless rows in Excel spreadsheets is impossible; hence the need for visualization Similarly, finding actionable patterns and relationships in databases accessed by a multitude of distinct applications is impossible Have you experienced being unable to find a value in an Excel spreadsheet that you know is there? Taming Big Data with Visual Analytics

Visual Analytics Example
Corvelle Consulting 4/19/2017 Visual Analytics Example Visual Analytics Example This graph may look busy but it brings all the data you need to make informed decisions together in one place at one time The data includes: Gross revenue Total expense Net back or gross margin Realized unit price or $/BOE You don’t have to engage in mental contortions to see the whole picture The key trend here is that profitability is trending down because unit sales price is trending down more steeply than operating costs are trending up Many analytic situations wrestle with the interplay of multiple variables This interplay becomes confusing very quickly Visual presentation helps us to understand the issue/opportunity Taming Big Data with Visual Analytics

Visual Analytics Leading Software Tools
Corvelle Consulting 4/19/2017 Visual Analytics Leading Software Tools Visual Analytics - Leading Software Tools These are the current leading software tools for Visual Analytics All have received excellent reviews These tools work well in all industries These vendors are embroiled in a software arms race to outdo each other on feature, function, integration, end-user development productivity Many vendors are consuming truckloads of venture capital dollars for software development and acquisitions An interesting feature of this list is the absence of Excel On one hand Excel does not meet the widely accepted definition for Visual Analytics Tools On the other hand many organizations rely exclusively on Excel for analytics tasks If we include Excel on this list, Excel becomes the product with the largest install base, larger than all the software shown here combined Do you have any of these installed at present? Can you share any experience with your use of these tools? What’s important to remember is that these are all tools These software tools won’t deliver any value straight out of the box You must first explain your data, explain your problem and describe how you want the problem analyzed This development work can be a daunting task for which a huge amount of business expert effort and developer effort will be consumed All these vendors incorporate excellent, high-productivity development tools into their products to make this task better, faster, cheaper Nonetheless, this development work carries the usual risks associated with software development Smarter Analytics Taming Big Data with Visual Analytics

Magic Quadrant for Business Intelligence and Analytics Platforms
Corvelle Consulting 4/19/2017 Challengers Leaders Magic Quadrant for Business Intelligence and Analytics Platforms Gartner - Magic Quadrant for Business Intelligence and Analytics Platforms Gartner has published an excellent report that contains lots of detail that supports this graph I highly recommend reading it before you license any software package in this space Niche Players Visionaries Taming Big Data with Visual Analytics

Oil & Gas Analytics Calgary Software Vendors
Corvelle Consulting 4/19/2017 Oil & Gas Analytics Calgary Software Vendors Oil & Gas Analytics - Calgary Software Vendors These are the current leading analytics applications in the oil & gas industry All have received excellent reviews Guild One SynergyStudio is a data exploitation solution that transforms data into strategic information assets through reports that are easily understood, shared and exploited to enhance business performance P2 Energy Solutions Qbyte Optix performance reporting tool provides fast, intuitive access to financial and production data. Information can be shared online, via PDF, Excel, or through links to reports. Templating allows you to create and save multiple customized Excel download templates making future downloads even simpler and faster. Superior ad-hoc reporting is facilitated through our modern database design, built considering our customers need to query data in unique ways with different production period dimensions. Trident Solutions Inc. Intelli-Worx is a reporting and analytics solution designed using the latest technology to specifically meet the reporting requirements of the oil & gas industry VISAGE VISAGE is an interactive visual analytics application designed and built for oil and gas producers It seamlessly integrates proprietary and public data sources The huge advantage these applications have over the tools on the previous slide is: The applications already understand the database schemas of the software packages you are using; therefore the install and integrate time is measured in only a small number of days as opposed to weeks or months The applications arrive with an understanding of the Canadian oil & gas business with many analytical functions already built-in and ready to use These four vendors offer oil & gas analytics software applications that are unmatched by anything found elsewhere on the planet when it comes to richness of functionality at a modest price point Calgary is a unique marketplace on the planet when we consider oil & gas software packages including analytics software A significant number of oil & gas producers are concentrated downtown creating an excellent market for software vendors Many oil & gas producers have installed some of these software packages from a small number of choices The Canadian oil & gas industry benefits enormously from regulator-mandated data submission requirements and from standards defined by organizations like ASC, CAPP, CAPLA, PPDM, PSAC, PASC and SEC Do you have any of these applications installed at present? Can you share any experience with your use of these applications? Taming Big Data with Visual Analytics

Visual Analytics Trends
Corvelle Consulting 4/19/2017 Visual Analytics Trends Machine learning Data discovery platforms Chief Analytics Officers Data products Hadoop datastores Visual Analytics Trends What’s in the future for Visual Analytics? What do the trend forecasters see in their crystal balls? Machine learning Machine learning involves the semi-automated development of predictive and prescriptive models that improve over time The software learns how to better fit the data and separate signal from noise The leading machine-learning environments still need people to specify the variables that can enter models, adjust model parameters for better fits, and interpret content for decision-makers Data discovery platforms Technology environments that make big data manipulation relatively easy and inexpensive Hadoop or MapReduce datastores handle the data volume Specialized processing appliances boost speed and performance Chief Analytics Officers Chief Data Officers, Chief Science Officers or heads of Big Data An organization that creates a senior role for analytics, whatever the title, has likely done a productive thing It's focusing on doing more with data, generating insights, and putting those insights to use Data products Big data has spawned a wave of new data products and service offerings For example, GE places sensors in gas turbines, jet engines, and medical imaging devices and then services those products based on sensor data analysis Hadoop datastores, based on MapReduce and HDFS, replace enterprise data warehouses Big data threatens the future of the enterprise data warehouse (EDW) Many companies covet Hadoop clusters because their per-unit costs to store and process data are a fraction of EDWs' As a bonus, Hadoop platforms can also perform some processing and analytics tasks Hadoop momentum produced competitors including MarkLogic, Hortonworks and Cloudera Google may or may not release its internal technology called Dremel and BigQuery Taming Big Data with Visual Analytics

Value of Visual Analytics
Corvelle Consulting 4/19/2017 Value of Visual Analytics Make data-driven decisions “very frequently” Make decisions “much faster” than market peers Execute decisions as intended “most of the time” Value of Visual Analytics This list describes the value that Visual Analytics provides to help companies differentiate themselves as leading companies relative to their peers and competitors Make data-driven decisions “very frequently” as opposed to infrequently or decisions made based largely on experience or gut feel with limited or incomplete information The production engineers I work with currently have been frustrated by how often they’ve made investment decisions based on incomplete information; they recognize the risk For example, I wonder how many oil & gas acquisition decisions are based on gut feel with limited or incomplete information Make decisions “much faster” than market peers as opposed to more slowly or even ponderously This concept is often called speed to insight It’s important because in many competitive situations, the first or fast mover ends up with most of the market share For example, I was impressed how quickly CNRL made the multi-billion dollar offer to Devon to buy the Canadian conventional assets Execute decisions as intended “most of the time” as opposed to having decisions be derailed, become sidetracked or stall out during execution For example, I notice that merger projects are often deemed complete even when the work is far from complete because the budget has run out or because of organization fatigue To our client this value amounts to millions of dollars in incremental net revenue per year without adding: More dollars to the capital budget More staff to the operating budget I hope some opportunities to employ visual analytics in your business are popping up in your mind Any ideas you might want to share? Taming Big Data with Visual Analytics

Integrated Analysis: Comparison of Actuals Sales to Estimates
Corvelle Consulting 4/19/2017 Integrated Analysis: Comparison of Actuals Sales to Estimates Integrated Analysis: Comparison of Actuals Sales to Estimates A picture is worth a thousand rows of data, allowing you to identify the areas of greatest concern This visual shows a scatter plot of percent variance vs. volume variance between estimated sales volumes (from field data capture) and actual sales volumes (from accounting) The two areas outlined are where the variance percent exceeds 15% and the volumes are considerable Now your business analysts can focus their attention on a targeted group of wells With good visual analytics software, the effort to create this chart is measured in minutes; with Excel and data access or integration issues you are looking at hours or days Taming Big Data with Visual Analytics

Recommendations Improve your data management processes
Corvelle Consulting 4/19/2017 Recommendations Improve your data management processes Identify operational problem Select visual analytics software package Pilot software package for problem Build on pilot success Recommendations Here are some recommendations to consider Improve your data management processes Visual analytics illuminates data quality problems that undoubtedly exist across your various databases that underlie your application portfolio Expect to allocate some resources to data quality Identify an operational problem You can likely identify a few operational problems that could be addressed by bringing better data to the workstations of key staff involved Pick one problem that’s modest in scope and where the business is demonstrating some interest, energy and leadership Select a visual analytics software package Select a visual analytics software package to pilot Select an application in preference to a tool if a credible application exists for your industry Pilot the visual analytics software package to address the operational problem Ensure functional management interest/sponsorship Train a small team Build the visual artefacts that will help the staff address the problem Build on pilot success Assuming the pilot is a success, plan to rollout the visual analytics product across more departments Taming Big Data with Visual Analytics

Questions & Discussion
Corvelle Consulting 4/19/2017 Questions & Discussion Questions & Discussion Can you help us implement visual analytics? Please fill out evaluation form Taming Big Data with Visual Analytics

Taming Big Data with Visual Analytics
Corvelle Consulting 4/19/2017 Taming Big Data with Visual Analytics Yogi Schulz Partner of Corvelle Consulting Information technology related management consulting Microsoft Canada columnist & CBC Radio host Industry presenter PPDM Association board member Corvelle Consulting 300, Ave. S. W. Calgary, Alberta T2P 0L6 Phone: (403) Web: Taming Big Data with Visual Analytics Taming Big Data with Visual Analytics

Visual Analytics Software Packages Selection Criteria
Corvelle Consulting 4/19/2017 Visual Analytics Software Packages Selection Criteria Visual exploration Augmentation of human perception Visual expressiveness Automatic visualization Visual perspective shifting Visual perspective linking Collaborative visualization Visual Analytics Software Packages - Selection Criteria These are very unusual software selection criteria but I think they are important to software in the visual analytics category The leading software tools and applications I’ve referenced can all handle the more common software selection criteria such as: Can the software access the various databases and data formats I have in my organization? Can the software produce the visualizations and dashboards I need? Can the software perform the calculations I need? Can the software produce the reports I need? Can my development staff learn the tool reasonably easily? The Gartner Magic Quadrant for Business Intelligence and Analytics Platforms includes an excellent set of selection criteria Visual exploration – Querying, exploring and visualizing data occurs in a single process Augmentation of human perception – Visual thinking is encouraged and developed – the brain’s ability to process pictures far faster than text is leveraged Visual expressiveness – Visual displays have depth, flexibility and multi-dimensional expressiveness Automatic visualization – Effective visualizations are automatically recommended Visual perspective shifting – Shifting among alternative visualizations of any given data is effortless Visual perspective linking – Multiple images are intimately linked so that a selection on one image highlights related, relevant data on the other images Collaborative visualization – People can easily share and collaborate on useful information visualizations Taming Big Data with Visual Analytics

Bibliography – 1 Analytics Trends – 2014 by Deloitte
Corvelle Consulting 4/19/2017 Bibliography – 1 Analytics Trends – 2014 by Deloitte Big Data - Is your Data Warehouse a Dinosaur? Big Data: Issues and Challenges Moving Forward Big Data – The 4 V’s: The Simple Truth Big data and the E&P organization Bibliography – 1 Taming Big Data with Visual Analytics

Bibliography – 2 Big Data Focus on Value, Not Hype, in 2014
Corvelle Consulting 4/19/2017 Bibliography – 2 Big Data Focus on Value, Not Hype, in 2014 Big Data Market Size and Vendor Revenues Big Data Vendor Revenue and Market Forecast BIG DATA use cases – are there any “killer apps”? Big Data - What it is and why it matters Bibliography – 2 Taming Big Data with Visual Analytics

Bibliography – 3 Enterprise Business Intelligence Platforms, Q4 2013
Corvelle Consulting 4/19/2017 Bibliography – 3 Enterprise Business Intelligence Platforms, Q4 2013 Extracting Value from Chaos 5 Big Business Intelligence Trends For 2014 Four Big Data Challenges Four Ways to Illustrate the Value of Predictive Analytics Bibliography – 3 Taming Big Data with Visual Analytics

Corvelle Consulting 4/19/2017 Bibliography – 4 Gartner's Big Data Definition Consists of Three Parts, Not to Be Confused with Three "V"s Graph Analytics 101 How Can Graph Analytics Uncover Valuable Insights About Data? IDC Worldwide Business Analytics Software 2013 The knowledge society: The impact of surfing its tsunamis in data storage, communication and processing Bibliography – 4 Taming Big Data with Visual Analytics

Corvelle Consulting 4/19/2017 Bibliography – 5 Magic Quadrant for Business Intelligence and Analytics Platforms Selecting a Visual Analytics Application Solving Problems with Visual Analytics A Survey of Visual Analytics Techniques and Applications: State-of-the-Art Research and Future Challenges Ten Benefits of Business Intelligence Software Bibliography – 5 Taming Big Data with Visual Analytics

Corvelle Consulting 4/19/2017 Bibliography – 6 The 3 big problems in big data (hint: They all involve people) 3 Tips for Getting More Value From Your Data Top Business Intelligence Trends For 2014 TIBCO Spotfire® Ranked Highest “Current Offering” in Forrester Wave for Agile BI 2014 Upstream Tech holding a tin cup below a Niagara Falls of data! Bibliography – 6 Taming Big Data with Visual Analytics

Corvelle Consulting 4/19/2017 Bibliography – 7 The value of Big Data: How analytics differentiates winners Value, Velocity, Volume and Variety: Analyzing Big Data Views from the front lines of the data-analytics revolution Visual Analytics: Definition, Process, and Challenges Visual Display of Quantitative Information Edward Tufte Wisdom of Crowds® Small and Mid-Sized Enterprise Business Intelligence Market Study Bibliography – 7 Taming Big Data with Visual Analytics

Videos Big Ideas: How Big is Big Data? Big Ideas: Why Big Data Matters
Corvelle Consulting 4/19/2017 Videos Big Ideas: How Big is Big Data? Big Ideas: Why Big Data Matters Oil & Gas IQ - Understanding Big Data Power Your Performance! Big Data in the Energy Industry What is Big Data? What is Big Data? Part 1 & 2 Videos Taming Big Data with Visual Analytics

Corvelle Drives Concepts to Completion
Corvelle Consulting 4/19/2017 Corvelle Drives Concepts to Completion Taming Big Data with Visual Analytics

Visual Analytics Tool vs. Application
Corvelle Consulting 4/19/2017 Visual Analytics Tool vs. Application Characteristic Tool Application Pre-built integrations None Yes Pre-built analytical functions Required customer developer skills Significant Control over application development direction Complete High Analytical functionality limitations Some Visual Analytics - Tool vs. Application This list compares the Tool vs. Application approaches based on technical characteristics Pre-built integrations Tools come with no pre-built integrations; tools require the customer to define their vision and build their own integrations with databases Applications typically provide the integrations for the most common databases for their industry and can provide thought leadership and best practices Pre-built analytical functions Tools come with no pre-built analytical functions; tools require the customer to build their own analytical functions Applications typically come with a core set of analytical functions pre-built for the most common analytical questions of their industry Required customer developer skills Tools require the customer to either have or contract for significant developer skills Applications rely on the vendor’s developer skills and leverage their experience Control over application development direction Tools provide the customer with complete control over application development direction limited by the boundaries of the tool’s capabilities Applications provide the customer with high control over application development direction by directing the work of the vendor staff Analytical functionality limitations For tools, there are few analytical functionality limitations because the vendors have spent literally billions on development and acquisitions to make sure there aren’t On applications, there may be some analytical functionality limitations but we haven’t run into them yet Taming Big Data with Visual Analytics

Corvelle Consulting 4/19/2017 Visual Analytics Tool vs. Application Characteristic Tool Application Development elapsed time Variable Short Development risk Significant Low Production quality application Feasible but rare Yes Visual Analytics - Tool vs. Application This list compares the Tool vs. Application approaches based on technical characteristics Development elapsed time For tools, the development elapsed time is highly dependent on the availability, skills and experience of project staff For applications, the development elapsed time is highly dependent on the availability, skills and experience of vendor staff; however, since most of the work is configuration-oriented, the effort and therefore the elapsed time is short Development risk For tools, the development risk is significant because it’s dependent on the experience of business and project staff For applications, the development risk is low because very little development is contemplated Production quality application For tools, production quality applications are achievable through the extra effort and dollars required For applications, the software package should already have production quality features in terms of look & feel as well as operation and management functionality Taming Big Data with Visual Analytics

Corvelle Consulting 4/19/2017 Visual Analytics Tool vs. Application Characteristic Tool Application Elapsed time to initial value Variable Short End-user business knowledge High Low Ongoing dependence on vendor Some Influence on vendor software direction Significant Cross-industry Yes No Vendor stability risk Modest Visual Analytics - Tool vs. Application This list compares the Tool vs. Application approaches based on non-technical characteristics Elapsed time to initial value For tools, the elapsed time to initial value is highly dependent on the availability, skills and experience of project staff Applications tend to have the basic requirements for the industry well understood on arrival; this significantly shortens the elapsed time to initial value End-user business knowledge Tools require the customer to make in-depth business expertise available to define requirements to the project team that will build the analytical functions Applications are less demanding of in-depth business expertise point because the application already includes the benefit of in-depth business expertise Ongoing dependence on vendor For tools, the dependency on vendor staff is low unless you engage the professional services group for development Support for industry specific “how to build something” questions is not readily available Applications tend to have some dependence on vendor for support and configuration tasks. Support is focused on end user “how to use the application” Influence on vendor software direction For tools, the ability of a client to influence the software development direction of such large vendors is low On applications, the ability of a client to influence the software development direction of smaller, more local vendors is significant Cross-industry Tools can be used successfully in every industry Applications tend to be focused on the needs of one industry This difference may not be important because a given company tends to operate in only one industry Vendor stability risk For tools, the vendor risk is the risk associated with the turmoil that follows an acquisition or merger There is a high probability of mergers among these vendors as the visual analytics software market matures For applications, the vendor risk is the risk associated with the turmoil being acquired or merging There’s also the risk of failure due to mismanagement or being squeezed out of the market by one of the tool vendors Taming Big Data with Visual Analytics

Global Digital Information Created
Corvelle Consulting 4/19/2017 Global Digital Information Created Global Digital Information Created Zettabytes per year Taming Big Data with Visual Analytics

Sample Big Data Applications
Corvelle Consulting 4/19/2017 Sample Big Data Applications Sample Big Data Applications BIG DATA use cases – are there any “killer apps”? Taming Big Data with Visual Analytics

Enterprise BI Vendor Landscape
Corvelle Consulting 4/19/2017 Enterprise BI Vendor Landscape Enterprise BI Vendor Landscape Here’s how these 10 vendors are distributed by Info-Tech, an IT research organization Taken from slide 10 of file: it-Enterprise-BI-Vendor-Landscape-Storyboard.pptx from Info-Tech Taming Big Data with Visual Analytics

Value of Visual Analytics
Corvelle Consulting 4/19/2017 Value of Visual Analytics Eliminate guesswork Answer business questions better & faster Produce key business metrics consistently Build insight into customers & problems Learn how to streamline operations Improve efficiency Learn what your true costs are See where your business has been, where it is now and where it is going Value of Visual Analytics Ten Benefits of Visual Analytics Eliminate guesswork Far too often, executives rely on 'best guess' and 'gut feel' decisions as they attempt to steer their companies into the future Visual Analytics can provide more accurate historical data, real-time updates, synthesis between departmental data stores, forecasting and trending, and even predictive 'what if?' analysis This capability eliminates the need to guesstimate; reduces the risk of a wrong recommendation based on too little analysis under time pressure Answer business questions better & faster Visual Analytics users can quickly produce better answers to business questions Visual Analytics providers higher confidence that most of the alternatives have been thoroughly explored Visual Analytics reduces development cost and elapsed time This approach avoids spending hours reading through volumes of printed reports Produce key business metrics consistently Visual Analytics software makes it possible for users to access key business metrics consistently, reliably and repeatably period after period. Build insight into customer behavior One of the great benefits of Visual Analytics software is it allows companies to gain visibility into what customers are buying (or not). This insight gives companies the ability to turn this knowledge into additional profit and retain valuable customers. Identify cross-selling and up-selling opportunities Visual Analytics software allows companies to leverage customer data to build, refine and modify predictive models that help sales representatives to up-sell and cross-sell products at appropriate customer touch points. Learn how to streamline operations With detailed insights into business performance, companies can easily see where they need to make changes to streamline operations. Improve efficiency With Visual Analytics software, all the information is centralized and can be viewed in a dashboard or turned into a report, saving enormous amounts of time and eliminating inefficiencies. Learn what your true costs are Visual Analytics software can give end-users greater insight into costs and the ability to adjust production on the fly for greater profitability. Manage inventory better Visual Analytics software can help you order the right amount of inventory at the right time so that customers receive their products when they need them. Your business doesn't bear the cost of stocking excess inventory. See where your business has been, where it is now and where it is going Visual Analytics is very successful at explaining what happened in the business and develop a realistic forecast for the future. Taming Big Data with Visual Analytics

Oil & Gas Data Warehouse Context Diagram
Enerplus 4/19/2017 Oil & Gas Data Warehouse Context Diagram Avocet Production data Qbyte FM Financial data gDC Public well data WellView Proprietary well data Oil & Gas Data Warehouse Context Diagram Data warehouses: bring data together into a single authoritative view Highlight data quality issues for resolution Visual analytics software typically accesses data, from the listed systems, that is managed in the data warehouse WCFD Frac’ing data ValNav CAPEX forecast data Data warehouse Production Optimization Project

VISAGE Context Diagram
Enerplus 4/19/2017 VISAGE Context Diagram Update Data warehouse VISAGE Context Diagram VISAGE can either access the data warehouse or the underlying application datastores Config. data Summary data VISAGE Graphs Tables Reports Exports Production Optimization Project

Corvelle Consulting 4/19/2017 Any chance I could get better, faster, cheaper visual analytics instead? Taming Big Data with Visual Analytics

Taming Big Data with Visual Analytics

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Taming Big Data with Visual Analytics

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