How Big Data helps banks know their customers betterHEXANIKA
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Enterprises today mine customer data to ensure maximum success by targeting their products and solutions to the right audience. Let us have a look at how Big Data and Customer Analytics are helping businesses use their customer data for maximum benefits.
How Big Data helps banks know their customers betterHEXANIKA
Â
Enterprises today mine customer data to ensure maximum success by targeting their products and solutions to the right audience. Let us have a look at how Big Data and Customer Analytics are helping businesses use their customer data for maximum benefits.
How Artificial Intelligence is Impacting Marketing Today and How Smart Market...Mark Osborne
Â
Overview of Artificial Intelligence AI and Machine Learning technologies that are impacting marketing today, and how marketers can plan their career and build the relevant computer science / engineering / statistics / and data-driven decision-making skills to excel in the future. Covers relevant algorithms, and marketing strategies like segmentation, targeting, and positioning, and how marketers can prepare
Unlocking the Value of Big Data (Innovation Summit 2014)Dun & Bradstreet
Â
Big Data is central to the strategic thinking of todayâs innovators and business executives as companies are scrambling to figure out the secret to transforming Big Data to Big Insight and that Insight into Action. As many companies struggle with the emerging technologies and nascent capabilities to discover and curate massive quantities of highly dynamic data, new problems are emerging in the form of how to ask meaningful questions that leverage the âVâsâ of large amounts of data (e.g. volume, variety, velocity, veracity). In the Business-to-Business space, these challenges are creating both significant opportunity and ominous new types of risk. This presentation discusses how companies are reacting to these changes and provide valuable insight into new ways of thinking in a world with overwhelming quantities of data.
MTBiz is for you if you are looking for contemporary information on business, economy and especially on banking industry of Bangladesh. You would also find periodical information on Global Economy and Commodity Markets.
The enterprise marketer's playbook: Building an integrated data strategy.
An integrated data strategy can help any business see customer journeys more clearly â and then give customers more relevant ads and experiences that get results. So why doesn't everyone have such a strategy? We look at what sets the marketing leaders apart.
Let marketing data be your guide
If you've ever felt too swamped by data to find the customer insights you need, you're not alone. But there's a new and better approach to gaining deeper audience insights: building an integrated data strategy.
Read this report to learn how:
86% of senior executives agree that eliminating organizational silos is critical to expanding the use of data and analytics in decision-making.
75% of marketers agree that lack of education and training on data and analytics is the biggest barrier to more business decisions being made based on data insights.
Leading marketers are 59% more likely to use digital analytics to optimize the user experience in real time.
MIT report: How data analytics and machine learning reap competitive advantage.Nicolas Valenzuela
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How Analytics and Machine Learning Help Organizations Reap Competitive Advantage
Produced MIT Technology Review, in Partnership with Google Analytics 360 Suite
Etude PwC : "Digital Banking Survey" (2014)PwC France
Â
http://pwc.to/1jQNy0n
Le secteur bancaire ne doit cesser d'innover pour continuer de satisfaire les besoins de leurs clients au temps de la digitalisation. Retrouvez toutes les conclusions PwC sur ce sujet.
Big Data in Retail - Examples in ActionDavid Pittman
Â
This use case looks at how savvy retailers can use "big data" - combining data from web browsing patterns, social media, industry forecasts, existing customer records, etc. - to predict trends, prepare for demand, pinpoint customers, optimize pricing and promotions, and monitor real-time analytics and results. For more information, visit http://www.IBMbigdatahub.com
Follow us on Twitter.com/IBMbigdata
How Artificial Intelligence is Impacting Marketing Today and How Smart Market...Mark Osborne
Â
Overview of Artificial Intelligence AI and Machine Learning technologies that are impacting marketing today, and how marketers can plan their career and build the relevant computer science / engineering / statistics / and data-driven decision-making skills to excel in the future. Covers relevant algorithms, and marketing strategies like segmentation, targeting, and positioning, and how marketers can prepare
Unlocking the Value of Big Data (Innovation Summit 2014)Dun & Bradstreet
Â
Big Data is central to the strategic thinking of todayâs innovators and business executives as companies are scrambling to figure out the secret to transforming Big Data to Big Insight and that Insight into Action. As many companies struggle with the emerging technologies and nascent capabilities to discover and curate massive quantities of highly dynamic data, new problems are emerging in the form of how to ask meaningful questions that leverage the âVâsâ of large amounts of data (e.g. volume, variety, velocity, veracity). In the Business-to-Business space, these challenges are creating both significant opportunity and ominous new types of risk. This presentation discusses how companies are reacting to these changes and provide valuable insight into new ways of thinking in a world with overwhelming quantities of data.
MTBiz is for you if you are looking for contemporary information on business, economy and especially on banking industry of Bangladesh. You would also find periodical information on Global Economy and Commodity Markets.
The enterprise marketer's playbook: Building an integrated data strategy.
An integrated data strategy can help any business see customer journeys more clearly â and then give customers more relevant ads and experiences that get results. So why doesn't everyone have such a strategy? We look at what sets the marketing leaders apart.
Let marketing data be your guide
If you've ever felt too swamped by data to find the customer insights you need, you're not alone. But there's a new and better approach to gaining deeper audience insights: building an integrated data strategy.
Read this report to learn how:
86% of senior executives agree that eliminating organizational silos is critical to expanding the use of data and analytics in decision-making.
75% of marketers agree that lack of education and training on data and analytics is the biggest barrier to more business decisions being made based on data insights.
Leading marketers are 59% more likely to use digital analytics to optimize the user experience in real time.
MIT report: How data analytics and machine learning reap competitive advantage.Nicolas Valenzuela
Â
How Analytics and Machine Learning Help Organizations Reap Competitive Advantage
Produced MIT Technology Review, in Partnership with Google Analytics 360 Suite
Etude PwC : "Digital Banking Survey" (2014)PwC France
Â
http://pwc.to/1jQNy0n
Le secteur bancaire ne doit cesser d'innover pour continuer de satisfaire les besoins de leurs clients au temps de la digitalisation. Retrouvez toutes les conclusions PwC sur ce sujet.
Big Data in Retail - Examples in ActionDavid Pittman
Â
This use case looks at how savvy retailers can use "big data" - combining data from web browsing patterns, social media, industry forecasts, existing customer records, etc. - to predict trends, prepare for demand, pinpoint customers, optimize pricing and promotions, and monitor real-time analytics and results. For more information, visit http://www.IBMbigdatahub.com
Follow us on Twitter.com/IBMbigdata
Jahia CMO Kevin Cochrane presented at Gartner's Digital Marketing Conference about what it means to truly invest in customer experience (CX).
"Brands that win will focus on customer experience. They will bring back the human element. They will connect, protect and respect their customers. They will expand their focus beyond data-driven marketing and customer acquisition to the post-login experience.
In other words, they will make their customers smile."
Moving Forward with Big Data: The Future of Retail AnalyticsBill Bishop
Â
Out new report Moving Forward with Big Data: The Future of Retail Analytics goes deeper into new territory that's relevant to changes taking place across retailing.
It calls out significant progress in the past 9 months.
âą The definition of big data has grown beyond technical, i.e. âwhat it is,â to include âwhat it does.â
âą A lot more companies are executing big data projects (an increase from < 20% to now 65% of sample respondents).
âą Most of the focus is on driving top line growth.
PresentationThe capability of enormous information - or the new .pdfaradhana9856
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Presentation
The capability of enormous information - or \"the new oil,\" as a few CIOs and industry
specialists have named it - appears as perpetual as it is subtle. Huge information battles are in
their early stages, with endeavors of all stripes making sense of how to utilize new, old,
unstructured and outer information to make a focused procedure.
Despite the fact that the standard procedures for get-together information and investigating its
value are as yet coming to fruition, organizations know they have to get in the diversion. They
are gathering and mining information on clients, workers, market flow, the climate, and so on,
with instruments going from conventional business insight (BI) frameworks to more trial ones,
for example, geospatial and constant versatile following innovations, online networking
investigation and NoSQL databases.
SearchCIO isn\'t remaining on the sidelines, either. Our Essential Guide on enormous
information incorporates a preliminary for beginning with information social affair and
investigation, true contextual investigations from the CIO and business viewpoints, tips on the
best way to beat hindrances experienced by the huge information pioneers, and expectations on
the following huge information boondocks and what it implies for aggressive methodology.
This aide on the development of huge information is a piece of SearchCIO\'s CIO Briefings
arrangement, which is intended to give IT pioneers vital administration and basic leadership
guidance on opportune themes.
The most effective method to Collect Big Data ?
1 year agoby Ayush1 Comment
The most effective method to Collect Big Data ? : Yes we knoe you would have various inquiries
in your psyche like Collection of Big Data, How organizations gather Big Data, how to gather
information for quantitative research so don\'t stress, in the event that you are here to scan for
these inquiries here then you are on the right website page as here we are going to give you a
complete article on Collection of Big Data techniques quickly.
Astounding Facts about Rise of Big Data Collectection
Consistently buyers make around 11.5 million installments by utilizing Paypal
Consistently, Walmart (chain of rebate retail chains) handles more than 1 million client
exchanges
510 remarks, 293000 status and 136000 overhauls are posted on Facebook consistently
Consistently, ~7000 tweets are made on Twitter
Simply picture the measure of information created if the above details are figured for 24 hours?
Whoa! That is huge.
The term \'Enormous Data\' is ordinarily connected with 4V\'s to be specific, Velocity, Volume,
Variety, Veracity. These 4V\'s appropriately speaks to the genuine way of Big Data. Each \"V\"
has a noteworthy part to play in the presence of Big Data. On the off chance that consolidated,
these 4V paints a wonderful clarification of Big Data which can be comprehended as \" Big Data
as an idea alludes to high speed gathering of information in expansive volumes which radia.
Every day, enterprises across the globe are engaged in two key activities: delivering effectual effects and building decisions that create impact. If you are in the big business of building enterprises that will be more valuable in future than present your decisions need to be driven by smarter data.
Companies today are witnessing a huge explosion in data availability - 90% of the worldâs data was formed in the most recent years. Structured, semi- structured and unstructured data across internal business systems and external sources like social
media, market data and syndicated study are now creating an incredible opportunity to construct insights, therefore leading to intelligent decisions. However, as this data is generally available to an enterpriseâs competitive set, only those who have a vision for
leveraging this intellect and are adept will eventually out-compete others.
What Big Data Means for PR and Why It Matters to UsMSL
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Invited to sit on a panel together with Paul Holmes at the PR Forum held in Bucharest March 26, Pascal shared thoughts about the Big Data tsunami which is deeply transforming marketing, communications and PR. What is "Big Data" exactly, what does it mean to businesses, why does it matter to us, and what potential issues could arise from it?
The concept of Big Data emphasizes the use of the complete data set to analyze process and predict various phenomena in the business world. This document describes the business uses of Big Data and outlines a Strategy for implementing Big Data analytics for Social Media
Is Your Company Braced Up for handling Big Datahimanshu13jun
Â
Has your company recently launched new product or company is concerned with the poor sales figure or want to reach new prospects and also reduce the existing customers' attrition, then this thought evoking short hand guide is available for you to explore.
Mid sized companies dont have sensors and machines spitting out big data, but they have lots of data from traditional sources like CRM, ERP and Billing software. How do you use this. Some techniques, examples and case studies from other industries to get your creatives flowing
Create the engagement your customer wants and the outcomes your business needs. We had this published behind an email wall, but now making it public for everyone.
The new âA and Bâ of the Finance Function: Analytics and Big Data - -Evolutio...Balaji Venkat Chellam Iyer
Â
Published in 2013, this White Paper discusses how the finance function would evolve with the combined forces of Big Data and Analytics and the levers that could help catalyze the change and has drawn upon the Global Trend Study conducted by Tata Consultancy Services (TCS) on how companies were investing in Big Data and deriving returns from it.
Another great content/horrendous stock photo "presentation" from IT Business Edge about Big Data. (http://www.itbusinessedge.com/slideshows/big-data-eight-facts-and-eight-fictions.html)
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
Â
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Â
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
đ Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
Â
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
Â
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Â
Clients donât know what they donât know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clientsâ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
Â
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more âmechanicalâ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Â
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
DevOps and Testing slides at DASA ConnectKari Kakkonen
Â
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
Â
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Â
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Free Complete Python - A step towards Data Science
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Anatomy of the new decision
1. Anatomy of the New Decision
How Five Hot Trends Are Shaping the Future of
Business Analytics
A White Paper
WebFOCUS iWay SoftwareWebFOCUS iWay Software
2. 1 Introduction
3 Predictive Analytics: Back to the Future
3 Predictive Modeling and Analytics
5 Outsourced Data for Better Insights
6 (I Love Analytics) for Sentimental Reasons
8 Big Decisions Require Big Data
9 Mobile BI: BYOD FTW
11 Anatomy of the New Decision
11 Law Enforcement
12 Retail
13 Solutions From Information Builders
13 Intelligence
13 Integration
14 Integrity
15 Conclusion
Table of Contents
3. Information Builders1
Introduction
For decades, companies have made decisions based on instinct, hunches, and intuition. Then
came business intelligence (BI), which made decision-making more scientific. Before it was known
as BI, it was referred to as âdecision support.â Companies would review the data they had collected
and make decisions about the future based on what had happened in the past. For example:
â â A two-year, increasing trend of sales in Florida dictates the need to increase inventory levels over
last year in that region to meet demand
â â A law enforcement agency deploys more of its officers to District A, one its highest crime areas
â â Students with higher SAT scores have higher graduation rates than students with lower scores,
so to improve graduation rates, a university only accepts students with higher SAT scores
That kind of thinking was good â once. Nowadays, itâs like fighting with one hand tied behind
your back.
Each of the decisions above was made using a small number of data points to conjure up an
overly simplistic conclusion. Smarter decisions would incorporate more relevant data that answers
more sophisticated questions, such as:
â â What products or services have Florida customers been most positive about on social
networking, blogs, and free-form feedback sites?
â â What factors â such as weather, special events, and economics â influence various types of
crimes and where they are likely to occur today?
â â What are the likely consequences of increasing the average SAT score in the acceptance process?
The good news is that exciting technologies are now emerging, and in some cases, converging,
to help organizations drive innovation, which empowers people to make smarter decisions with
insight based on more than just structured, static data. Behind the tech industry buzzwords,
there are practical and proven methods for applying these new technologies to your current
information management strategy and unlocking measurable returns:
â â Cloud-based information services enable us to get information that a company might not have
previously tracked on its own, such as demographic and market changes in Florida
â â Predictive analytics combines many factors to present a clear picture of whatâs most likely to
happen, what is the best-case scenario, and what action should be taken
â â Social media analytics help us to understand how other people are reacting to our actions â far
more quickly and reliably than focus groups would
â â Big data technologies help us to manage the increasing velocity, variety, and volume (the three
Vs) of all of the data that makes this possible
â â Mobile computing deploys analytics to more people, so they can make smarter decisions
whenever and wherever they are
4. Anatomy of the New Decision2
Moreover, the technology advancements are more effective when used in concert than when
taken separately.
In this paper, we will discuss how cloud-based services, predictive analytics, social media analytics,
big data, and mobile computing are combining to take business intelligence beyond traditional
boundaries and transform the way critical decisions are made. We will also highlight Information
Buildersâ solutions and share two use cases, which demonstrate how two organizations â a law
enforcement agency and a retailer â might use available tools and technologies to tap into the
wealth of information available.
5. Information Builders3
Queries, reports, dashboards, and other forms of business intelligence are often used to answer
simplistic questions: What product mix was sold this month compared to last month? What are
the year-over-year overhead expense trends?
OLAP and query tools have allowed users to refine and enrich those comparisons, but while the
tools have gotten better, faster, and easier to use, the basis for how they facilitate decision-making
based on historical data hasnât changed much.
Predictive analytics changes the game by going beyond an analystâs current viewpoint and
providing new, sophisticated insight about how the past can help predict the future.
Predictive Modeling and Analytics
Predictive analytics is often misunderstood. It doesnât conjure up miraculous forecasts from thin
air. Instead, it correlates the relationships between many factors (most commonly descriptive
dimensional and numeric data) and provides insight into which of those factors may influence
an outcome. That influencing effect can then be given a score or a probability, which becomes a
âpredictive analytic.â
The choice of factors affects decision-making the most. For instance, scouting in baseball has
always been based on metrics such as stolen bases, RBI, and batting average, but it took the
statistical analysis headed up by Billy Beane, general manager of the Oakland Aâs, to recognize that
on-base percentage and slugging percentage were more predictive markers of offensive success.
Predictive Analytics: Back to the Future
Predictive data mining supports retail initiatives such as target marketing,
cross- and up-selling, and customer acquisition and retention.
6. Anatomy of the New Decision4
Beane could find those qualities more cheaply on the open market, and was thereby able to
assemble a team competitive with the best in the league â for about a third of the payroll cost.
Convenience store transactions might be affected by weather, with in-store ATMs generating
walk-in traffic when outdoor ATMs are less pleasant to use. Used car sales might be affected by
the local real estate rental market. Generic medication prescriptions might see an uptick after a
marketing campaign by a brand-name pharmaceutical company.
The point isnât that any one of these things is true or false; itâs that you wouldnât know whether
they were true or false unless you assembled the data and found out where the statistical
correlations are. That modeling, and the predictions that come from it, lead to business value.
7. Information Builders5
With predictive analytics, it can be a challenge to collect enough data while ensuring its relevance
to outcomes. For example, many organizations have failed to collect certain historical data outside
their own sphere of influence â but that external or third-party data may have a significant
influence on their outcomes. After all, who would expect weather to impact retail sales or crime
rates? Why would a company collect stock market trends or changes in tax rates to see if they
affect automobile sales?
But these factors really can affect business results. When the marketing arm of a national retailer
analyzes how sales were affected by a Presidentsâ Day promotional campaign â but doesnât take
into account a serious storm system in the southeastern U.S. â it might reduce its efforts in Florida
when it should be increasing them.
This problem isnât limited to predictive analytics, either. Any form of analytics will be limited by the
available data.
Fortunately, there are information providers for almost any kind of information you can think of,
and cloud-based web services allow users to unify historical data with information about the
weather, crime, the stock market, travel trends, taxes, and virtually anything else. Integrating cloud-
based external data resources with unstructured input from social networks enables companies to
dramatically improve the sophistication of their decision-making without having to collect every
possible external factor that might affect their businesses.
Outsourced Data for Better Insights
8. Anatomy of the New Decision6
Sellers used to have a chance to talk to potential customers before they made a decision about
what product to buy. Those days are gone. In business-to-business sales, more than 60 percent of
a typical purchasing decision now happens before the buyer ever contacts a supplier.1
Buyers arenât talking to sellers because theyâre talking to each other. Social networks and blogs
have made it very easy for them to get information about products and services that interest
them. Itâs incredibly important for businesses to discover what theyâre thinking about their
products, services, marketing campaigns, salespeople, return policies, customer support, and
anything else that reflects on them. In other words, they need the ability to do sentiment analysis
about their company, brands, executives, and campaigns.
One influential person tweeting â[brand] is horrible!â can have a devastating effect. A few dozen
Facebook posts complaining about on-hold times or product limitations can deter future buyers.
On the other hand, a vibrant customer community that is nurtured to provide positive statements
will move potential customers into the buyersâ camp. A brand that listens and responds to
customer issues with honesty and transparency can establish even closer relationships based
on trust.
PepsiCo is a great example of a company that understands the power of social insight. It has used
social networks to gather customer insight about its DEWmocracy promotions, which have led to
the creation of new varieties of its Mountain Dew brand. Since 2008, the company has sold more
than 36 million cases of them2
.
The best news of all is that companies can now analyze sentiment continuously, at a fraction of
the cost of other methods, while incorporating sentiment information into other forms of analysis.
Social media sentiment analysis can replace or augment $15,000 phone surveys, $7,000 mail
surveys, and $6,000 focus groups â while catching problems before they get out of control.
(I Love Analytics) for Sentimental Reasons
Accurately understand customer sentiment and visualize the context of the
words used to describe your company, products, and services.
9. Information Builders7
As Forresterâs Zach Hofer-Schall says, âSocial mediaâs prevalence across the web gives consumers
and brands a new way to connect online. But while most businesses know the importance of
social media, most are missing opportunities by not capturing and analyzing the data generated
in social channels.â3
Imagine how different the analysis of a Presidentsâ Day promotion might look if, instead of just
looking at the timing of the promotion, it also took into account both the weather and the
sentiment of tweets that contain a related hashtag. Understanding social engagement through an
integrated use of data, tools, and technologies is a clear priority for all organizations for amplifying
customer loyalty, competitive differentiation, and growth.
1 Adamson, Brent; Dixon, Matthew; Toman, Nicholas. âThe End of Solution Sales,â Harvard Business Review,
August 2012.
2 Dival, Roxane; Edelman, David; Sarrazin, Hugo. âDemystifying Social Media,â McKinsey Quarterly, McKinsey
Company, April 2012
3 Hofer-Shall, Zach. âLeverage Social Data To Elevate Customer Intelligence,â Forrester, May 2012.
10. Anatomy of the New Decision8
Data volumes are growing rapidly, for many reasons. Predictive analytics are most reliable on
very large data sources. Blog posts and social media can encompass a huge amount of language.
Sensor data (everything from smart utility meters in your house to RFID chips in warehouses) has
made certain things possible, while increasing data volumes dramatically. The mobile channel has
spawned a whole new category of data to track, from in-app clicks to mobile transactions.
And that just accounts for one of the âthree Vsâ of big data.
A recent study by the Economist Intelligence Unit, commissioned by Capgemini, found that
two-thirds of respondents â 607 global executives (43 percent of them C-level and board
executives) from 20 different industries â say that the collection and analysis of data underpins
their firmâs business strategy and day-to-day decision-making. In fact, just more than half say that
management decisions based purely on intuition or experience are regarded as suspect.4
Because there seems to be value in big data, many companies start collecting massive volumes of
diverse, real-time data before they know what to do with it. Unfortunately, they donât necessarily
make sure that itâs clean at collection time. Ideally, data is clean as transactions flow into your
systems, such as when the user clicks âOKâ on your website or as an RSS feed tells you that a new
blog post is live.
Moreover, having data quality tools helps to correlate information from multiple systems. For
instance, companies may improve their one-to-one marketing dramatically if they can determine
that âjdoe1968â on their website is âJonathan Doe,â who used a credit card on the phone last
month and also identified himself as âJon Doeâ just now when he entered a store in Manhattan.
Finally, if a companyâs data is truly big, most people will need help in finding the information or
analytics that derive from it. Theyâll need a search engine thatâs fully populated with structured
data, unstructured data, and links to existing reports and analysis.
Big Decisions Require Big Data
4 Olavsrud, Thor. âBig Data Analytics Today Lets Businesses Play Moneyball,â CIO, August 2012.
11. Information Builders9
The new decision isnât chained to a desk.
Information is our constant companion: at meetings, in coffee shops, or first thing in the morning
if thatâs when we need it. How we interact with information can be very personal â so much
so that we now expect to interact with our personal laptops, smartphones, and tablets to get
answers to business questions. As a result, itâs more important than ever that business intelligence
be available on any device, whether iOS, Android, or BlackBerry, and in virtually any form factor.
There are a couple of ways that the mobile channel impacts decision-making and, when
combined with a few of the other tech trends weâve discussed, can be a total game changer.
First, mobile apps can be designed to empower your employees with real-time information â
and the ability to analyze that information on the fly and on the go. By optimizing data analytics
for mobile platforms, and incorporating the native capabilities of the mobile devices, you
are empowering users, creating a personal connection to your brand for all key stakeholders,
improving efficiency, streamlining communications, and differentiating your services.
But there is also a âback-officeâ side to mobile that can improve our understanding of our
business so that we make better strategic decisions about its operations, marketing, and finances.
Smartphones are essentially sensors that enable you to get location- and context-aware feedback
from a variety of touchpoints in real time. When you combine this mobile data with other
data sources (i.e., big data) and apply analytics, the result is a whole new understanding of the
workforce, the customer, and the market.
Mobile BI: BYOD FTW
Mobile BI enables you to check critical data at any time, from any location.
12. Anatomy of the New Decision10
Interestingly, this increased emphasis on mobility also increases the emphasis on data quality.
When someone shares information with a lot of people, it had better be right. And since mobile
data also needs to come from every kind of system so people donât have to wait to get to their
desks to get the real answer, mobile applications also increase the need for data integration.
13. Information Builders11
The new decision â one that leverages predictive analytics, as well as data from cloud and
social media sources â applies to many real-world scenarios. From financial institutions trying
to put together the most successful portfolio of products and services to telecommunications
companies seeking new and effective ways to increase loyalty, the new decision provides insight
that can drive competitive advantage.
Lets look at two potential use cases â one in law enforcement and another in retail.
Law Enforcement
The image above represents a city divided into six sectors. Each sector is color-coded based on
historical crime data: Sector B has the highest crime rates, followed by sectors C, F, D, E, and A.
Standard historical crime analysis would indicate that the police dispatcher would need to put the
greatest police presence in sector B to help deter crime. However, todayâs event calendar shows
that there is a free concert in sector A. The concert starts at noon in the city park, with 5,000
attendees expected, but the weather forecast shows a 60 percent chance of rain. This typically
means that there will be at least a 50 percent drop-off in concert attendance.
In the past, when the forecast has called for rain, the crimes that commonly occur in sector B tend
to decrease, while occurrences of petty theft in the shopping mall parking lots in sector F increase.
Anatomy of the New Decision
A
B
C
D
E
F
14. Anatomy of the New Decision12
A look at public sentiment on the cityâs Facebook page, as well as on various local blogs, shows
that many people are concerned with the high number of traffic accidents taking place on the
main highway leading into the city in sector E. An astute analyst also notices that activity on the
bandâs Facebook page (the band playing the free concert) suggests that there is going to be an
âafter partyâ at one of the nightclubs near the concert in sector A â meaning additional police may
be needed hours after the concert concludes.
This information shouldnât automate every decision the dispatcher makes â people should still
be in control of critical decisions â but it can crystallize the factors that should affect his choices.
Predictive scoring may tell him that he needs more coverage in sector A at the concert and near
the after party hours later, and heâll choose to fulfill that need with foot patrols. Meanwhile, heâll
reallocate traffic police to cover sector E on the highway, and deploy police on bicycles in sector F
in the parking lots of the shopping mall.
Retail
A large retailer sells an average of 100 cases of water each week. However, predictive models
that include weather data show that stores in the southwest will sell nearly twice as many cases
when temperatures soar above 90 degrees. Since temperatures are expected to be high for the
next week, the retailer can adjust its forecasts accordingly. The same retailer has also found that
outlets within five miles of a large body of water (where boating is a common pastime) tend to
sell nearly three times as many marine-grade nuts, bolts, and fasteners as outlets in other areas.
This information was discovered using a web service that provides maps and distances for specific
addresses and points of interest.
Store managers can also monitor a real-time dashboard that displays recent posts on the
companyâs Facebook page. These posts are solicited via a large sign at each checkout counter,
asking shoppers to comment on their experience. The dashboard allows managers to track sales
and shopper sentiment, so they can quickly adjust staffing and labor levels accordingly, to ensure
optimum service.
The bottom line is that making decisions is not always a black-and-white, yes-or-no effort.
A decision itself can be a complex array of smaller decisions that combine to produce a
desired result.
Information shouldnât automate every decision â people should still
be in control of critical decisions â but it can crystallize the factors that
affect those decisions.
15. Information Builders13
Information Builders designs and develops high-value solutions that help companies to boost
revenue by providing unmatched integration of enterprise information assets, dramatically
improving the integrity of the data contained in those assets, and transforming that data into
powerful intelligence for wide-scale use.
Intelligence
The WebFOCUS BI platform combines broad data access with unparalleled usability, scalability,
and low cost of ownership to make information and analytics readily available and easily
consumable to an unlimited number of internal and external users. WebFOCUS features:
â â Powerful BI that makes reports, queries, and dashboards available to power and business users
â â Advanced analytics, visualization, location intelligence, and enterprise search to enable accurate
customer analysis, revenue forecasting, price simulation, and more
â â Comprehensive performance management that aligns strategy with key performance indicators
(KPIs), and balances them against risk
â â The ability to build once, and deploy across all online and mobile channels for a consistent user
experience
â â Innovative sentiment analysis to help companies mine data from social media sites, and analyze
it to accurately assess customer opinion
Information Buildersâ Intelligence solutions also offer unparalleled scalability, reliability, and ease of
use. So companies can rapidly and economically create and deploy comprehensive, yet intuitive
self-service systems that meet the information needs of thousands, tens of thousands, and even
millions of external customers.
Integration
iWay Software Integration solutions from Information Builders help you to collect every kind
of information, whether you need it in real time or for historical purposes. iWay supports
unstructured data, such as blog posts and social media streams; cloud-based data from web
services or API queries; structured data from enterprise resource planning (ERP), customer
relationship management (CRM), legacy, and other systems; or sensor data, such as RFID or UPC
scans and utility gauge readings. With iWay, organizations can empower real-time decision-
making for competitive advantage and revenue optimization. iWay Integration solutions provide:
â â A robust integration infrastructure that allows companies to rapidly and economically build
broad-reaching integration architectures
â â Data integration solutions that facilitate coordination and cohesiveness across even the most
diverse and disparate information environments
â â A comprehensive universal adapter suite that contains pre-packaged integration components
to provide direct, native access to more than 300 sources, including data, applications, B2B
interactions, and cloud-based systems
Solutions From Information Builders
16. Anatomy of the New Decision14
â â Big data solutions that support high-performance data stores, such as IBM Netezza, Oracle
Exadata, SAP HANA, Teradata and Teradataâs Aster Data, EMC Greenplum, HP Vertica, 1010data,
ParAccel, and Kognitio, as well as MapReduce databases such Hadoop and MongoDB
With iWay, itâs easy to take data from every kind of system and bring it to your mobile apps â
whether the information is cloistered away in legacy systems or stuck inside proprietary ERP and
CRM applications, whether itâs big data or many tiny transactions, and whether day-old data is
okay or you need it in real time. The most time-consuming and labor-intensive step of mobile app
development â information integration â is cut short dramatically with iWay Integration solutions.
Integrity
iWay Integrity solutions include data quality capabilities that can help you create a data quality
firewall, ensuring the quality of data before it spreads into other parts of your enterprise. The
result is better operational processes, better BI, and â as the data moves into the realm of big data
â better correlated and managed big data analytics. iWay data integrity solutions also provide
master data management (MDM) technology that can correlate disparate information from very
different system types â and can be overseen by data stewards, who can even manage data from
their mobile devices. iWay data integrity solutions comprise:
â â Data quality management tools, with an automated rules engine, for creating a real-time data
quality firewall that proactively preserves information integrity
â â Master data management to synchronize disparate data sources and create a single, golden
record for each product, customer, patient, or citizen
â â Data governance solutions that provide end-to-end control over how information is managed as
it is collected, used, and maintained
17. Information Builders15
The examples in this paper demonstrate how complex effective decision-making can be. Because
a variety of factors influence outcomes, straightforward âyesâ or ânoâ answers simply donât exist.
Every decision is made up of an array of smaller choices, which will impact the eventual result.
Decision-makers go through great pains to make sure they have gathered all of the appropriate
data to make a well-informed decision.
What is different today is that the new decision can be made with more complete data, more
easily, and in less time than before. The people making those decisions have the means to take
all influencing factors into account, and weigh them based on their relevance, importance, and
impact. The new capabilities outlined in this paper mean less time is spent gathering data, and
more time is given to mulling over the influencing factors, so they have an appropriate amount of
time to use their experience and intuition to make the best decision.
More and more companies are arming their employees with business intelligence tools, like
Information Buildersâ WebFOCUS, and iWay Integrity and Integration solutions, to help them with
these types of data-influenced decisions. And as more and more data â primarily from social
media vehicles, mobile channels, and other Internet sources â becomes available for use by those
tools, the accuracy and effectiveness of those decisions will continue to increase rapidly.
Conclusion