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.
25. RIGHT BRAIN
CONCLUSIONS
1. Accelerated learning 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
27. Cognitive products
and services
Cognitive products 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
A Do-It-Yourself
mentality now prevails
Expectations from technology have never been higher
Our work and personal
lives have blurred
30. Even a simple analytics 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 rarely a straightforward process
Business
Users Data Scientists
and
Statisticians
IT
Data Access
Analysis
Validation
Collaboration
Reporting
Data Preparation
Business
Analysts
32. Think Ahead
Tell a Story
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 Data Scientists IT
Self-service analytics for business users and
experts alike
Business Users
34. Empowering the business for success
Prioritizing
Accounts
Receivable
Employee
Retention
Helpdesk
Case
Analysis
Campaign
Planning and ROI
Warranty
Analysis
Customer
Retention
Finance HRITMarketing OperationsSales
35. “Which accounts are most 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
Watson Analytics 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.
39. Single Analytics Experience
Fully Automated Intelligence
Natural Language Dialogue
Guided Analytic Discovery
Visit WatsonAnalytics.com
and get started for free
40. 1. A cognitive strategy
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
Text to
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
44. Certus are helping customers build an
Information Architecture that stores,
explores and analyses data in new
ways.
45. New Architecture to Leverage 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
Information Server 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 using cutting edge
matching to give companies a 360
degree view of customers, students,
products or assets
48. Maximize 1:1 consumer
relationships
Deliver personalized 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 Warehouse CRM 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
› Inspect potential 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
Decreased risk
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 helping customers 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
56. Monitoring Quality and Stewardship 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 has helped
customers manage
data quality via a
policy driven
approach.
Data Quality Scorecards
57
59. Quality and Lineage behind a report
Data lineage
track back,
quality of each
asset in lineage
Data Quality
trends over time
Quality Metrics
60. QSuper Success Story
IBM Insight 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
Hinweis der Redaktion
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.
125,000 sold in 2001
Useful Content
We can understand who this lady is influenced by and as well who she inspires…
Fiction vs Fact.
Dream vs Reality.
Brand can shape reality, in just the same way as fiction can shape fact.
Fiction vs Fact.
Dream vs Reality.
Brand can shape reality, in just the same way as fiction can shape fact.
Fiction vs Fact.
Dream vs Reality.
Brand can shape reality, in just the same way as fiction can shape fact.
Fiction vs Fact.
Dream vs Reality.
Brand can shape reality, in just the same way as fiction can shape fact.
Fiction vs Fact.
Dream vs Reality.
Brand can shape reality, in just the same way as fiction can shape fact.
Fiction vs Fact.
Dream vs Reality.
Brand can shape reality, in just the same way as fiction can shape fact.
Fiction vs Fact.
Dream vs Reality.
Brand can shape reality, in just the same way as fiction can shape fact.
Fiction vs Fact.
Dream vs Reality.
Brand can shape reality, in just the same way as fiction can shape fact.
Fiction vs Fact.
Dream vs Reality.
Brand can shape reality, in just the same way as fiction can shape fact.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.