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Just ask Watson Seminar
This document discusses cognitive computing and analytics technologies. It provides examples of how cognitive systems can be applied, such as a toy that learns from child interactions. The document outlines a cognitive strategy and foundation that includes collecting and analyzing both structured and unstructured data. It also discusses the importance of cloud services, infrastructure, and security for cognitive systems. Finally, the document describes some of the cognitive computing APIs available from IBM Watson and how the set of APIs has expanded over time.
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Just ask Watson Seminar
- 1. NORMAL SERVICE WILL NOTRETURN
- 2. JUST ASK WATSON CognitiveRevolution
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- 5. Wireless Smart Devices Anywhere Anytime Anything 2015: Onemobile device for every human
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- 20. Accelerated learning platform… OBSERVATION #ONE Whereit will lead I don’t know. However I believe…
- 21. Recommendation It is theintersection between AI + BI OBSERVATION #TWO
- 22. • Human • Machine •Expert OBSERVATION #THREE
- 23. Creating entirely new possibilities…not yet thought of OBSERVATION #FOUR
- 24. OBSERVATION #FIVE Enabling entirely different approachesto: • Building applications • Mine data • Achieve meaningful outcomes
- 25. RIGHT BRAIN CONCLUSIONS 1. Acceleratedlearning platform 2. This is the intersection between AI + BI 3. Human + Machine + Expert 4. Creating entirely new possibilities not yet thought of 5. Enabling entirely different approaches to building applications, mining data + achieving business outcomes…. staying competitive
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- 27. Cognitive products and services Cognitiveproducts and services can sense, reason and learn so they can adapt and develop new capabilities not previously imaginable. THE POSSIBILITIES OF COGNITIVE: Elemental Path, a Watson ecosystem partner, developed Cognitoy, a dinosaur toy, that answers its playmate’s questions, and even learns their sense of humor by listening to and adapting its personality to play differently with each child. Results: Cognitoy is able to take on a unique personality that evolves over time based on the child’s interactions and helps her learn rhyming, spelling, vocabulary, mathematics and more. WHERE WE ARE NOW: Decision management platforms will expand at a CAGR of By 2018 Apps with advanced and predictive analytics are growing of all consumers will regularly interact with services based on cognitive. 50% faster than apps without predictive functionality. 65% 60% through 2019, in response to the need for greater consistency and knowledge retention.
- 28. It’s an “always-on” world ADo-It-Yourself mentality now prevails Expectations from technology have never been higher Our work and personal lives have blurred
- 29. Making decisions rapidlyis no longer a goal; it’s an imperative The desire to make data- driven decisions is prevalent Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute for Business Value study. Copyright © Massachusetts Institute of Technology Access to required data sources is critical while maintaining governed standards 34% can not find time to analyze data 38% have a limited understanding of how to use analytics Leveraging analytics still faces many obstacles 24% find it difficult to get data
- 30. Even a simpleanalytics project has multiple steps and people Data Access Data Preparation Analysis Validation Collaboration Reporting Business Analysts Business Users Data Scientists and Statisticians IT
- 31. And it’s rarelya straightforward process Business Users Data Scientists and Statisticians IT Data Access Analysis Validation Collaboration Reporting Data Preparation Business Analysts
- 32. Think Ahead Tell aStory Understand Your Business Get Better Data Mobile Ready Secure Embedded information services provide data access and refinement Automated intelligence accelerates your ability to answer questions Predictive analytics reveals insights and opportunities Visualizations support your decisions and communicate results Put analytics in the hands of a broad range of users Make data access and refinement easier Deliver through the cloud for agility and speed
- 33. Business Analysts DataScientists IT Self-service analytics for business users and experts alike Business Users
- 34. Empowering the businessfor success Prioritizing Accounts Receivable Employee Retention Helpdesk Case Analysis Campaign Planning and ROI Warranty Analysis Customer Retention Finance HRITMarketing OperationsSales
- 35. “Which accounts aremost likely to be paid? How can collections be more efficient? How does it affect revenue and profit when we lose customers? How can the sales pipeline help me forecast revenue?” Justin Chen, Finance Manager
- 36. Justin Chen Customer attrition WatsonAnalytics analyzes customer data to identify which customers are likely to leave and why and predicts the effect on revenue. Justin can then determine which customer investments will lead to more profitable growth.
- 37. Natural language dialogue Cloud-based agility Data discovery Quickstart intuitive interface Mobile- ready
- 38. Unified analytics experience Visual storytelling Intelligent automation Dataaccess and refinement Report and dashboard creation Integrated social business Guided analytic discovery
- 39. Single AnalyticsExperience Fully Automated Intelligence Natural Language Dialogue Guided Analytic Discovery Visit WatsonAnalytics.com and get started for free
- 40. 1. A cognitivestrategy Determine what data you need, which experts will train the system; where you must build more human engagement; which products, services, processes and operations should be infused with cognition, and which parts of the unstructured 80% of data you most need to focus on to make discoveries for the future. 2. A foundation of data and analytics Collect and curate the right data—data you own, data from others, data available to all; both structured and unstructured. Apply cognitive technologies to this data in order to sense, learn and adapt, thereby creating competitive advantage.3. Cloud services optimized for industry, data and cognitive APIs The building blocks for products and services are code, APIs and diverse data sets. The platform you choose to develop on, and the agile development culture and methods you embrace, will be critical to your success. 4. IT infrastructure tuned for cognitive workloads Architect a new kind of IT core—a heterogeneous infrastructure that serves as the backbone of your enterprise. Do this rapidly and affordably by harmonizing technologies from public, private and hybrid cloud with distributed devices, IoT instrumentation and your existing systems. 5. Security for a Cognitive Era As cognition makes its way into cars, buildings, roadways, business processes, fleets, supply chains—securing every transaction, piece of data, and interaction becomes essential to ensure trust in the entire system—and in your brand and reputation.
- 41. Relationship Extraction Questions & Answers Language Detection Personality Insights Keyword Extraction Image Link Extraction Feed Detection Visual Recognition Concept Expansion Concept Insights Dialog Sentiment Analysis Textto Speech Tradeoff Analytics Natural Language Classifier Author Extraction Speech to Text Retrieve & Rank Watson News Language Translation Entity Extraction Tone Analyzer Concept Tagging Taxonomy Text Extraction Message Resonance Image Tagging Face Detection Answer Generation Usage Insights Fusion Q&A Video Augmentation Decision Optimization Knowledge Graph Risk Stratification Policy Identification Emotion Analysis Decision Support Criteria Classification Knowledge Canvas Easy Adaptation Knowledge Studio Service Statistical Dialog Q&A Qualification Factoid Pipeline Case Evaluation The Waston that competed on Jeopardy! in 2011 comprised what is now a single API—Q&A—built on five underlying technologies. Since then, Watson has grown to a family of 28 APIs. By the end of 2016, there will be nearly 50 Watson APIs— with more added every year. Natural Language Processing Machine Learning Question Analysis Feature Engineering Ontology Analysis
- 43. CERTUS CUSTOMER EXAMPLES Bringingtechnology, people and processes together
- 44. Certus are helpingcustomers build an Information Architecture that stores, explores and analyses data in new ways.
- 45. New Architecture toLeverage All Data and Analytics Data in Motion Data at Rest Data in Many Forms Information Ingestion and Operational Information Decision Management BI and Predictive Analytics Navigation and Discovery Intelligence Analysis Landing Area, Analytics Zone and Archive Raw Data Structured Data Text Analytics Data Mining Entity Analytics Machine Learning Real-time Analytics Video/Audio Network/Sensor Entity Analytics Predictive Exploration, Integrated Warehouse, and Mart Zones Discovery Deep Reflection Operational Predictive Stream Processing Data Integration Master Data Streams Information Governance, Security and Business Continuity
- 46. BigInsights Hadoop Data Platform Sources InformationServer Data Integration Watson Data Exploration BI / Analytics Break the “Waterfall Style” Lifecycle • Empowers LOB to access data sooner • Eliminates slow modeling prior to staging Analytics Performance Booster • Leveraging Teradata for its strength • Less wasted process, fewer batch windows Lower Cost Staging, ELT and Deep Data • Commodity infrastructure for data platform • Automated data transformation and governance Fresh Capacity and Cost Avoidance • Recoup previously displaced disk • Defer costly upgrades for production uses Improving Integration for Analytics
- 47. Certus are usingcutting edge matching to give companies a 360 degree view of customers, students, products or assets
- 48. Maximize 1:1 consumer relationships Deliverpersonalized offers aligned to unique behaviors, needs and desires Brand reputation Right message every time in market Marketing productivity Increased breadth of digital channels, emphasis on cross-sell / up-sell / right- sell opportunities, understanding and embracing ROMI Deliver value across all touch points Build opportunity for revenue growth throughout marketing value chain 360 Degree View of the Customer Understanding, responding and maximizing each unique customer relationship Optimize marketing mix Model and plan balancing needs of channels, probability of ROI success and resource constraints Customer growth and retention Demanding customers, commoditized products and crowded competitive marketplace Define MDM Value
- 49. Consuming Applications Contact WarehouseCRM MarketingPortal Kate Lamb 32 George Street Perth, 6000 Kate Jones Perth, WA 6000 12/06/1970 Catherine Jones 44 Station Street Perth, WA Mrs K Lamb 32 St. George 06/12/1970 Dr Katherine Lamb 23 George St Perth, 6000 06/12/1970 Miss C Jones Station Street, Perth Western Australia, 6000 12/06/1970 Person Entity Dr. Katherine Lamb Composite View Dr Katherine Lamb 32 George St, Perth, WA 6000 DOB: 12/06/1970 Probabilistic Matching
- 50. Household relationships › Inspectpotential household members and link to confirm relationships. Employment Relationships › Inspect relationships between companies and staff. Joseph’s Household Wife of Daughter of Son of Is the Subsidiary of Supplies Product to Is Married to Is the Owner of Has an Account with Is Employed by Entity Relationships
- 51. Big Match ›The same MDM Match engine runs on Hadoop to connect more sources of information about the customer.
- 52. Increased engagement Increased revenue Decreasedrisk Less ‘gut feel’ More data (when used effectively) Increase on Churn retention rate (no discounting required) More newsletter article clicks More articles read per session Lookalike acquisition model increasing conversion Strong Ad revenue growth 20% 10% Linkage: audience connections Any hard links across accounts, Consumer & Household, Fuzzy matching, Enrichment (Single Customer View) MDM Value – News Corp Presentation to IBM SolutionConnect Event Sydney 2014
- 53. Certus are helpingcustomers put in successful data stewardship models to trust the results they get from reporting and analytics.
- 54. Technology Driven Process Driven 1)Define Business Problem 2) Obtain Executive Sponsorship 3) Conduct Maturity Assessment 4) Build Roadmap 6) Build Business Glossary 7) Understand Data 8) Create Metadata Repository 5) Establish Organizational Blueprint 9) Define Metrics 11) Govern Master Data 10) Govern Data Quality 14) Govern Analytics 13) Govern Security & Privacy 12) Govern Lifecycle of Information 15) Measure Results
- 55. Business Glossaries thatExtend to Big Data
- 56. Monitoring Quality andStewardship Tasks Data Quality Dashboard › Data Quality Metrics across lines of business that makes quality relevant to everyone. Stewardship Center › Manage a team of stewards and allocates data quality investigation and data remediation tasks.
- 57. › Certus hashelped customers manage data quality via a policy driven approach. Data Quality Scorecards 57
- 58. How do Itrust a report?
- 59. Quality and Lineagebehind a report Data lineage track back, quality of each asset in lineage Data Quality trends over time Quality Metrics
- 60. QSuper Success Story IBMInsight Conference 2015 Operational Impact › Productivity improvements through automation of data checking reporting. › Data checking is consistency applied › Increased confidence in data › Workloads can be managed and anticipated › KPI’s can be applied Regulatory Impact › Risk and Compliance reporting is measurable and can be monitored › Mitigating risk of penalties and fines through more accurate reporting › Industry leader in data quality activities. 60
Editor's Notes
- #6 900 million smart phones will be sold this year Next year will see one-mobile enabled device for every human on earth. That’s 7 billion.
- #7 125,000 sold in 2001
- #8 Useful Content
- #13 We can understand who this lady is influenced by and as well who she inspires…
- #18 Fiction vs Fact. Dream vs Reality. Brand can shape reality, in just the same way as fiction can shape fact.
- #19 Fiction vs Fact. Dream vs Reality. Brand can shape reality, in just the same way as fiction can shape fact.
- #20 Fiction vs Fact. Dream vs Reality. Brand can shape reality, in just the same way as fiction can shape fact.
- #21 Fiction vs Fact. Dream vs Reality. Brand can shape reality, in just the same way as fiction can shape fact.
- #22 Fiction vs Fact. Dream vs Reality. Brand can shape reality, in just the same way as fiction can shape fact.
- #23 Fiction vs Fact. Dream vs Reality. Brand can shape reality, in just the same way as fiction can shape fact.
- #24 Fiction vs Fact. Dream vs Reality. Brand can shape reality, in just the same way as fiction can shape fact.
- #25 Fiction vs Fact. Dream vs Reality. Brand can shape reality, in just the same way as fiction can shape fact.
- #26 Fiction vs Fact. Dream vs Reality. Brand can shape reality, in just the same way as fiction can shape fact.
- #29 The world is changing, what do we as individuals see differently now? Expectations are increasing: At work and at home, we expect technology to deliver immediate access to the information we seek. As the lines between our personal and work lives blur, we’re expected to know more, understand more and do more. If the technology we use doesn't provide value immediately, we simply drop it and move on to the next thing. Make better decisions faster: We live and work at a relentless pace, and we’ve never been more connected to the people, brands and information that matter to us most. With the intense speed of business today, time—or more clearly, our “return on time”—has become a primary currency by which many measure value. Making better decisions rapidly is no longer a goal; it’s an imperative. We must shrink the time to informed action, which requires us to deliver more than just faster answers; it demands that we identify the right questions to ask. Do it yourself thinking: We’ve become a global society that practices independent investigation and pervasive learning. Have a question? Get an answer…quickly, simply, and on your own. The data is there, and so are the technologies that make it easy to identify, explore, verify and share that information. This freedom breeds creativity in how we approach problem-solving, even as it fuels expectations that we can consistently deliver fast, correct action.
- #30 We now find the characteristics we have come to expect in our daily lives should carry over into our job roles. However, there are obstacles preventing widespread adoption of analytics within businesses. Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute for Business Value study. Copyright © Massachusetts Institute of Technology Departmental experts and analysts are expected to drive better data-driven decisions, but lack the breadth of advanced skills needed for data management, building predictive models, and effectively communicating the correct conclusions. Self-service is increasingly becoming more important as business users are pressured and motivated to quickly find answers on their own. Making decisions rapidly is no longer a goal; it’s an imperative. Reducing the time to informed action requires a streamlined ability to draw compelling conclusions without reliance on too many people and the need to leverage multiple disparate tools. Self-service needs are increasing, and organizations are concerned about maintaining corporate data governance standards and security. The expectation of today’s workforce is that they can access and analyze their data anytime, anywhere. And then getting insights to decision-makers quickly is critical to delivering fast, correct action.
- #31 Even a simple analytics project has multiple steps and people. Projects require multiple steps in order facilitate and adhere to the policies or practices that are important to the business process. However its rarely straight forward and does not address the needs of rapid and agile data exploration and discovery.
- #32 Projects require multiple steps like accessing and obtaining data. Business units and individuals from IT and departmental analysts are needed to manage and govern data sources. Providing this data to Analysts takes time and resources. Validation of this data is critical to avoid errors and poor decision making before the data is reviewed and approved for its original intent. If the data is wrong then the reporting will be wrong and decisions will be inadequate.
- #33 We have arrived at a tipping point where the abundance of data, emergence of cloud, advances in analytics, new user experience design and business models mean data-driven decisions can now be an essential, daily and valuable activity for business people. No longer just for data scientists or IT -- marketing, sales, operations, finance and HR professionals can gain answers they need from all types of data. This requires a revolution in analytics technology, helping people acquire, refine data, discover insights, predict outcomes, visualize results, create reports, and collaborate with others in a unified user experience that speaks the language of business. Introducing IBM Watson Analytics. Watson Analytics offers automated data preparation and intelligence, engaging storytelling and guided predictions so you can find answers and action in your data on your own. No matter what part of the organization you’re in. Watson Analytics is such a revolution - a revolution in the techniques themselves and a further revolution in the convergence of all these technologies together. The result will be widespread adoption of advanced analytics in the business world. IBM Watson Analytics delivers a unified analytics experience on the cloud and helps you focus on the drivers that matter most in your business. By automating the steps of data access and refinement, predictive analysis, and visual storytelling, Watson Analytics immediately identifies and explains hidden patterns and relationships to accelerate your understanding of why things happened and what's likely to happen. Because Watson Analytics features natural language dialogue, you can ask the right questions and get results in the familiar terms of your business. Just as the first spreadsheet made financial calculations easier for anyone with a PC, Watson Analytics opens up the world of advanced analytics to all business users on the cloud. Think ahead Watson Analytics helps you go where your ideas take you with guided and predictive analytics and recommendations. Pursuing ideas, answering questions, making predictions, and deciding what to do next should be as easy as using an app on your smartphone. And you shouldn’t need help from IT or expertise from data scientists. With Watson Analytics, making decisions, anticipating outcomes and taking action can now be a smooth and interesting process. And, if you aren’t sure what you need to do, Watson Analytics automatically starts you off with ideas and guides you through analysis so you can find meaning in your information and make better decisions. It even introduces additional capabilities you might find useful as you become bolder and want to dig deeper. Make more informed decisions to move your business forward. Tell a story Visualization is the illustration of trends and patterns in your data so they can be understood. It is a critical capability of analytics. Having the right visualization can make the difference between seizing the right opportunity and making a sketchy decision. However, choosing just the right one can be tricky. Watson Analytics recommends the visualizations that illustrate what’s important the most effectively and brilliantly. You can use these visualizations to create infographics that advance understanding and communication and spur the right action. Ask questions and receive answers in the language you use in your business. Understand your business Watson Analytics jumpstarts your analysis. It automates intelligence to accelerate your ability to get to the answers you’re seeking. It immediately starts you off with a visual story that illustrates what you need to know. Instead of fumbling over data or searching for answers, you can focus on understanding your business and effectively communicating results to others. Simply type in what you would like to see and Watson Analytics produces comprehensive results that explain why things happened and what's likely to happen, all in familiar terms. And as you interact with the results, you can continuously fine-tune your questions to get to the heart of the matter. Tell a clear, insightful story through rich data visualization. Get better data Built into Watson Analytics are information management services for data access, refinement and management. Cloud-based data management services automatically find, acquire and improve data sets with the touch of a button. And, the latest in columnar and in-memory technology handles large volumes of data with ease. Watson Analytics can also score the readiness of your data for analysis, highlighting potential data issues that could compromise results. What does this mean for you? Basically, you don’t have to worry about the state of your data. Watson Analytics is designed to make sure the right data is ready when you are. With automation and embedded data refinery services, you get better data and better understanding. Whether you are in marketing, sales, IT, operations, HR or finance, you have the trusted data and intelligence you need to complete your projects. Take advantage of automation — from data preparation to analysis.
- #34 Who is Watson Analytics for? Watson Analytics offers self-service capabilities to the full range of business users and experts alike: -Individual Business Users, like sales operations, marketing programs managers, financial analysts, or operations managers, who are looking to better understand the data relevant to their job roles; -Business Analysts, whose jobs are centered around processing information for the organization, and who want to go beyond measuring and start understanding, but don’t have ready access to advanced analysts such as data scientists, statisticians, data miners, or BI architects; and -Data Scientists themselves who can spend 40-80% of their time on data access and refinement. Watson Analytics can be an accelerator for them. -IT, who can deliver improvements in productivity to business users without having to support multiple solutions, ungoverned data sources, or rogue data analysis projects. What issue or opportunities does Watson Analytics address? The world and the way people work are changing: Departmental experts and analysts are expected to drive better data-driven decisions, but lack the breadth of advanced skills needed for data management, building predictive models, and effectively communicating the correct conclusions. Making quality decisions rapidly is no longer a goal; it’s an imperative. Reducing the time to informed action requires a streamlined ability to draw compelling conclusions without reliance on too many people and the need to leverage multiple disparate tools. Self-service is increasingly becoming more important as business users are pressured and motivated to quickly find answers on their own. Self-service needs are increasing, but IT is concerned about maintaining corporate data governance standards. The expectation of today’s workforce is that they can access and analyze their data anytime, anywhere. And then getting insights to all stakeholders quickly is critical to delivering fast, correct action.
- #35 Watson Analytics can be used for a wide variety of business use cases. Here are just a few examples such as: Marketing Lead Prioritization: Increase the quality of leads in your sales pipeline by discovering the driving factors of leads that resulted in successful sales. Target leads and prospects that will have a higher likelihood of becoming a sale to boost revenue and reduce costs by not spending time and resources on leads with little chance of becoming a sale. Customer Value Analysis: Customer growth improves overall profitability of the business and drives increased customer value and loyalty, delivering value-added products and services to an organization’s existing customer base. This is accomplished by first discovering the attributes that drive profitability, identifying what customers meet the identified profitable profiles, and then proactively providing those customers with highly targeted recommendations across all customer interaction channels to drive an increase in conversions and customer profitability Campaign Prediction and Planning: Improve effectiveness and efficiency in marketing departments by predicting which customers will respond to various campaigns. Predictive analytics provides value by increasing the quality of leads and the likelihood of response while reducing costs by efficiently targeting the customer through the right channel with the right offer at the right time. Sales Win/Loss Prediction: Analyze your sales pipeline and predict with confidence which deals have the highest chance of closing and those you’re at risk of losing to allocate resources effectively. Anticipate performance gaps in your sales pipeline, analyze current conditions and alternatives, and then optimize outcomes for predictable sales performance. Customer Retention: Predict which customers will leave and present customers' level of risk. Watson Analytics provides value by increasing customer retention and increasing the effectiveness of customer retention programs by targeting those customers most at risk of leaving. Finance Account Receivable Prioritization: Leverage Watson Analytics for collections. Organization can optimally determine their customers least likely to pay to most likely and prioritize their outreach and communication to align with their collections goals and objectives. By identifying the right customers to contact (and through which channel) organizations can improve operational efficiency and recover more money: a bottom line affect on income. IT Help Desk Activity Analysis: Analyze the IT help desk tickets in your organization. See how long tickets have been open, what the average response time is, and understand what the key drivers are of high priority tickets to help determine how to allocate resources to resolve tickets faster. Operations Warranty Claims Analysis: Analyze returns and predict upcoming warranty costs and issues, as well as determine potential fraudulent warranty claims. Increase the effectiveness of claims and warranty departments by improving the bottom line, decreasing costs, and enhancing supplier relationships. HR Employee Retention: Provide insight into workforce and human resource issues. Human Resource analysts can uncover predictive factors driving employee attrition allowing you to intervene and take appropriate action.
- #38 What are the features of Watson Analytics Self-service for Business Users Watson Analytics removes the reliance on DBAs, Statisticians, Report Authors or other specialists to do analysis. Its intuitive interface and unique automation of data access and refinement, advanced analytics and visual storytelling empowers business users to do more by themselves, like having a Data Scientist in a Box. Start anywhere, and let your curiosity take you wherever you want to go. Watson Analytics suggests where you might want to go next, progressively exposing you to additional capabilities you might want to leverage to gain a deeper understanding of your business. Differentiator Business users want a consumer-like experience to use analytics and data to pursue ideas, get answers to all types of questions, make predictions, and communicate compelling recommendations without needing help from anyone. However, they are hampered by the usability of analytics tools, access to data and dependency on others – both IT to provide the infrastructure and data scientists to provide the analytical expertise. With Watson Analytics, data-driven decisions can now be an essential, daily and interesting activity for business people. Data Discovery Watson Analytics lets you visually explore and interact with your data to find the obvious patterns and derive useful insights. Guided Analytic Discovery Watson Analytics features the use of predictive analytics to surface the most relevant facts and uncover unforeseen patterns and relationships. This sparks the right questions to ask and directs your attention to the parts of their business that matter most. Differentiator Most discovery solutions expect you to decide what’s important in your data for further analysis. Watson Analytics lets you explore as well, but often business users aren’t sure what type of analysis would be the most meaningful. Watson Analytics automatically surfaces what matters most in your business. You can then use that insight to guide your analysis. Cloud-based Agility Watson Analytics is available anytime, anywhere on the cloud. Mobile-ready Watson Analytics is optimized for tablet devices for analysis on-the-go. Natural Language Dialogue Watson Analytics speaks the language of your business. Simply type in what you would like to see and Watson Analytics produces comprehensive results that explain why things happened and what's likely to happen, all in the familiar terms of your business. And as you interact with the results, you can continuously fine-tune your questions to get to the heart of the matter. Differentiator Other offerings expect you to adapt to the software – speaking in some form of programming language. Watson Analytics lets you carry on a natural, iterative dialog using the terms that are meaningful to your business.
- #39 What are the features of Watson Analytics Single analytics experience Watson Analytics brings together a complete set of self-service analytics capabilities on the cloud. You bring your problem, and Watson Analytics helps you acquire the data, cleanse it, discover insights, predict outcomes, visualize results, create reports or dashboards, and collaborate with others. Differentiator Unlike other offerings that make you decide what type of analytics you want to do, and then select separate tools to accomplish it, Watson Analytics is a seamless, unified experience that lets you go where your ideas take you. For example, you can move seamlessly from discovery to predictive analysis – without changing user interfaces or losing work. Fully automated intelligence Just bring your data, and Watson Analytics will do the rest. By automating all the steps of data preparation, predictive analytics, and visual storytelling, Watson Analytics jumpstarts your analysis and accelerates your time to value. It immediately starts you off with a visual story that illustrates what you need to know. Instead of fumbling over data or searching for answers, you can focus on understanding your business and effectively communicating results to stakeholders. Differentiator Most analytic offerings assume you have data ready for analysis, a clear idea of the type of analysis you want to do, and the skills and time to build a model for analysis. However, most business users have none of these things. Data prep and loading can represent 60% or more of the time in an analysis project. Business users can spend a lot of time figuring out what analysis would be relevant and how to tell the story in a report or diagram. Watson Analytics automates these steps to accelerate your ability to get to the answers you’re seeking. Data Access & Refinement Watson Analytics automatically shapes and joins data and then uniquely scores the readiness of your data for analysis, highlighting potential data issues that could compromise results....(access to data, data shaping, data quality/cleansing, data masking) Integrated Social Business Watson Analytics help you to quickly and securely build consensus around your data-driven analytical findings. Overcome analysis paralysis by collaborating with all stakeholders to share, discuss, combine and build the evidence necessary to move forward on decisions. Reporting & Dashboarding Watson Analytics takes the guesswork out of how to best show what's important in your data and automatically recommends the most effective visualization to convey the results you are looking for. With a few clicks, users can further alter chart types and data to fully customize the interactive reports and dashboards to meet the needs of the business. Visual Storytelling Watson Analytics helps users to quickly consolidate and annotate key visualizations into powerful infographics to elegantly and effectively convey results to stakeholders.
- #40 Learn more about IBM Watson Analytics at WatsonAnalytics.com. Visit the site to get started with Watson Analytics for free. Register to access Watson Analytics on the cloud. Watch demos and how to videos, read content and talk to our experts through our community forum. Four key takeaway points: Watson Analytics brings together a complete set of self-service analytics capabilities on the cloud. You bring your problem, and Watson Analytics helps you acquire the data, cleanse it, discover insights, predict outcomes, visualize results, create reports or dashboards, and collaborate with others. Just bring your data, and Watson Analytics will do the rest. By automating all the steps of data access and refinement, predictive analytics, and visual storytelling, Watson Analytics jumpstarts your analysis and accelerates your time to value. It immediately starts you off with a visual story that illustrates what you need to know. Instead of fumbling over data or searching for answers, you can focus on understanding your business and effectively communicating results to stakeholders. Watson Analytics speaks the language of your business. Simply type in what you would like to see and Watson Analytics produces comprehensive results that explain why things happened and what's likely to happen, all in the familiar terms of your business. And as you interact with the results, you can continuously fine-tune your questions to get to the heart of the matter. Watson Analytics features the use of predictive analytics to surface the most relevant facts and uncover unforeseen patterns and relationships. This sparks the right questions to ask and directs your attention to the parts of their business that matter most.
- #46 Continue to flash forward, and we start to see a picture that depicts how Big Data technologies fit into an overall information architecture. Over 2013 and 2014 there were various flavors of this diagram which became known as the “Zones” diagram. I’m sure you’ve all see this before and likely have presented it to customer and partners. Of course, there were the inevitable questions about what products fit into which boxes, so there were versions of these zone diagrams that overlayed products onto the zones. Hadoop would be used for the Landing and Archive Zone, PureData, DB2, etc would be in the Warehouse and Mart Zones, Streams in real-time analytics. Etc. The thing to note is that these zones diagrams evolved from how the new technologies were actually being implemented in organizations around the world.
- #61 If current data cleansing activities are highly manual, the ability to conduct repeatable and consistent cleansing is significantly reduced. By introducing our Data Quality Framework which runs frequent automated routine of exactly the same data quality checks, exception management workload can be spread over the full year rather than be reactive. There are business process impacts as in automating the running of reports every week, the stewards are now performing less data checks but more often. By having the DQF generating tasks through a task management system, its also possible to track and measure how long it takes to correct the data and provide the actual cost of data cleansing activities. The biggest advantage of this is felt across both our internal and external impacts where Users running reports can be more confident in their accuracy as the timeliness of corrections is quicker. This means the provision of information is faster and lest costly for us to produce.