Customer Case Studies of Self-Service Big Data Analytics

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Self-service tools empowers business users to rapidly gather, analyze and visualize data from broad, diverse data sources. Analyzing these sources provides new answers and new business opportunities for those smart enough to answer the new questions. Free your IT staff from the need to respond to routine report requests. Business users can now rely on the rapid delivery of advanced self-service BI and data visualization capabilities to solve complex problems and capitalize on new opportunities. From these slides, you will learn: -Customer examples and return on investment from self-service big data analytics -How business analysts can take advantage of Machine Learning -Best practices in self-service big data analytics

Technology

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© 2013 Datameer, Inc. All rights reserved.

Big Data Analytics Use Case
Proﬁle!
Self Service
Large Datasets
Structured and Unstructured Data
Multiple Data Sources

© 2013 Datameer, Inc. All rights reserved.

Business Use Cases!
Customer
Analytics

Fraud and
Compliance

Operational
Analytics

EDW
Optimization

© 2013 Datameer, Inc. All rights reserved.

Legacy Modernization!
Traditional EDW!

18mo!

$1M+!

$1M!

Datameer on Hadoop!

12 wk!
3mo!

Time to Cost Per ! Salaries Time to
Build!
100TB! Required! Insights!

© 2013 Datameer, Inc. All rights reserved.

Time to
Build!

$400k!

$133k!

2d!

Cost Per
100TB!

Salaries
Required!

Time to
Insights!

Reduce Customer Acquisition
Costs
é

Customer acquisition
costs 30%

© 2013 Datameer, Inc. All rights reserved.

ê

Estimated $1.65M in savings

Optimize Funnel Conversion!
é

Customer Conversion
Increased by 60%

© 2013 Datameer, Inc. All rights reserved.

é

Revenue Increased
by $20M

Behavioral Analytics!
é

Increased
revenue by 2x

© 2013 Datameer, Inc. All rights reserved.

ê

Reduced IT
costs by 50%

Optimize Ad Impressions!
ê

Reduce ad impression costs $1M

Impression

Activity

Click

© 2013 Datameer, Inc. All rights reserved.

Identifying Potential Fraud!
ê $2B Credit Card Fraud
?
?
?
?

© 2013 Datameer, Inc. All rights reserved.

Compliance and Risk Analysis!
ê

Reduced analysis time
of over 300 attributes

© 2013 Datameer, Inc. All rights reserved.

Predictive Support!
é Proactive Customer Support
Component
Planning

Logs

Services

Id’d Product
Issues

Network
Data

Development
Unstructured
Logs

Accurate
Forecasting

111001

110010

01101001

01100100

10011101

01101110

Sales

© 2013 Datameer, Inc. All rights reserved.

Network Optimization!
é

$1M / hour
in peak holiday times

© 2013 Datameer, Inc. All rights reserved.

ê

Reduced network failure
by 30%, IT costs by 60%

Threat Prediction!
é

Avoid $5.5 M
in data breach costs

© 2013 Datameer, Inc. All rights reserved.

ê

Predict security threats
within hours instead of weeks

Optimizing Network Capacity!
ê

$150M in Savings in Capital Expenditures

© 2013 Datameer, Inc. All rights reserved.

Surveys reveal that concerns about data quality can create barriers for companies deploying Analytics and BI initiatives. How can you readily identify and correct data quality issues at every step of your big data analysis to ensure accurate insights into customer behavior? In this webcast, we'll discuss how IT and business users can leverage self-service visualizations to quickly spot and correct data anomalies throughout the analytic process. In this webinar, you will learn how to: -Continuously visualize a profile of your data to identify inconsistencies, incompleteness and duplicates in your data -Visualize machine learning and data mining, including clustering, decision tree analysis, column correlations and recommendations -Create self-service visualizations for business and IT users

Best Practices for Big Data Analytics with Machine Learning by Datameer

Datameer

Top 3 Considerations for Machine Learning on Big Data

Datameer

View the full recording of this deck here: http://info.datameer.com/Slideshare-Top-3-Things-to-Consider-for-Machine-Learning-on-Big-Data.html Machine learning is powerful but requires coding and access to all the relevant datasets to get full insights. With new Big Data analytic tools, business users can now use machine learning to gain a competitive edge. Based on best practices and customer experiences, join Datameer and Caserta Concepts as we discuss what to look for and what value organizations get out of Machine Learning on Big Data. This webinar will provide: *an overview of challenges and tools available today *use cases for machine learning on hadoop *capabilities to look for *comparison of available solutions

Datameer6 for prospects - june 2016_v2

Datameer

Datameer 6 is completely re-imagining the user experience for modern BI, helping you deliver new insights faster and more results to your data-hungry business. During this one-hour webinar, we demonstrated all that's new with Datameer 6 and how you can: Discover answers to a new range of business questions using an iterative, exploratory approach Find answers faster and deliver more insights with a new faster analytic workflow Utilize Spark to speed analytic processing time without needing to know technical details Watch this on-demand webinar, with special guest speaker, Sean Anderson, Senior Product Marketing Manager, from Cloudera, who discusses Cloudera's view of the Hadoop data processing stack and how the market place is benefiting from Spark.

Getting Started with Big Data for Business Managers

Datameer

Big Data has become critical to the enterprise because of the massive amount of untapped data sources, and the potential to gain new insights that were previously not possible. So, how to get started with Big Data and Hadoop becomes a question more pertinent than ever before. Listen to leading analyst at Ovum, Tony Baer, as he discusses answers to the key questions around how to: Approach Big Data and associated business challenges -- Identify what types of new insights can be revealed by Big Data -- Staff for this undertaking and implement the technology necessary to be successful -- Take the first steps toward getting started with Big Data on Hadoop

Webinar - Big Data: Power to the User

Datameer

What is the value of big data? How does a user get that value? Before, analysts would have to wait months relying on IT for a new report or make changes to an existing one. Now, analysts are able to shrink that time down to days or even minutes. On top of that, analysts can ask questions that were not possible before. In this webinar, we’ll show you how this analysis is possible and the value that has been achieved by customers. In this session, you will learn: How analysts get value out of big data How to visualize data at every step of analysis How analysts can do big data analytics without IT, in one product

Analyzing Unstructured Data in Hadoop Webinar

Datameer

Unstructured data is growing 62% per year faster than structured data. According to Gartner, data volumes are set to grow 800% in aggregate over the next 5 years, and 80% of it will be unstructured data. This on-demand webinar will highlight and discuss: How applying big data analytics to unstructured data can help you gain richer, deeper and more accurate insights to gain competitive advantages The sources of unstructured data which include email, social media platforms, CRM systems, call center platforms (including notes and speech-to-text transcripts), and web scrapes How monitoring the communications of your customers and prospects enables you to make time-sensitive decisions and jump on new business opportunities

This webinar featuring Claudia Imhoff, President of Intelligent Solutions & Founder of the Boulder BI Brain Trust (BBBT), Matt Schumpert, Director of Product Management and Azita Martin, CMO at Datameer, will highlight the latest technology trends in extending BI with big data analytics and the top high impact use cases. Attendees will hear about: -- The extended architecture for today's modern analytics environment -- The Internet of Things (IoT) and big data -- The evolution of analytics – from descriptive to prescriptive -- High impact use cases as a result of the changing analytics world

Modernizing Architecture for a Complete Data Strategy

Cloudera, Inc.

Data is the future of business. Either take advantage of it, or get surpassed by those who do. In this webinar, Ovum's Tony Baer discusses the importance of building a modern data strategy that ensures your journey with Apache Hadoop and big data is a successful one. Together, we'll walk through how to build a plan for long-term success while realizing short-term gains, including: How to pinpoint the business goals that matter most How to assess your strengths and weaknesses to meet those goals How to build a thoughtful approach that ensures your initiatives succeed

Webinar - Introducing Datameer 4.0: Visual, End-to-End

Datameer

In Big Data projects, analysts often spend 80% of their time preparing data for analysis. In addition, users don’t have a good understanding of their data quality. Today there are multiple tools that assist with integration, data preparation, analysis and visualization. However, data quality continues to be one of the biggest challenges businesses face when deploying big data analytics. People need to profile their data and ensure data quality to get accurate insights and make informed business decisions. Join Datameer as we address these pain points with visualizations at every step. This webinar will highlight and showcase: -How visual data profiling reduces the guesswork in the data wrangling process -Enhanced interactive data mining capabilities reduce time to insight -A demonstration of the new 4.0 features and functions

Unlocking data science in the enterprise - with Oracle and Cloudera

Cloudera, Inc.

Today, leading organizations struggle to make their data scientists productive in their modern data platforms. Data scientists find it difficult to use their existing open source languages (e.g. Python, R) and libraries with Hadoop, especially when the clusters are secured with Kerberos. At the same time, IT doesn't want to give special access to these users, who require very diverse and specific environment configurations to run their experiments. As a result, most data science teams work away from the big data cluster, often on their laptops or in other data silos. The negative business impacts are a lack of insight and agility for the most advanced users, and the security, governance, and cost issues that arise from data silos.

Optimize your cloud strategy for machine learning and analytics

Cloudera, Inc.

Join industry superstars Mike Olson (Cloudera CSO and co-founder) and Jim Curtis (451 Research senior analyst) as they outline the best practices for cloud-based machine learning and analytics in this “can’t miss” webinar. Hot topics include: Why enterprises are moving their analytics to the public cloud How to select the best cloud deployment model Design tricks that make cloud economics work Success stories, cautionary tales, and lessons learned James will share 451 Research findings and offer insights learned from surveying both the vendor landscape and enterprise practitioners. . Mike will regale you with his vision for the future of multi-disciplinary machine learning and analytics in hybrid- and multi-cloud environments 3 things to learn: Why enterprises are moving their analytics to the public cloud How to select the best cloud deployment model Design tricks that make cloud economics work

MapR Enterprise Data Hub Webinar w/ Mike Ferguson

MapR Technologies

Data volumes have experienced explosive growth in recent years, and that data is being generated from sources that are increasingly complex and varied. Harnessing and refining value from this data requires a new approach as data extraction, transformation, and loading (ETL) becoming increasingly more costly and difficult to scale. Organizations are looking to leverage Hadoop as an enterprise data hub—also called a “data lake” or “data reservoir”—as a key component of their data architecture to augment their data warehouse, ETL and analytical systems in order to maximize their existing investments, reduce costs, and unlock new business value from their data. In this webinar, you will learn: Real-world examples that illustrate why Hadoop is the best low-cost data hub, data lake, or data landing zone (staging area) option for ETL processing Proof points that demonstrate advantages of Hadoop and its ability to scale to manage increasing data volumes and support exploratory big data analytics Proven best practices for a cost-effective, reliable way to implement a data management platform for your entire big data analytical ecosystem Hidden issues to be aware of in deploying your data hub/data lake

Digital Government: Data + Government Isn't Enough | Wrangle Conference 2017

Cloudera, Inc.

Government agencies are collecting and producing data at an accelerating rate, and constituents want access to this data with decreasing latency. Meeting a digitally savvy polity's desire for data while ensuring that data is open, accessible, and interpretable by all comes with unique challenges. I'll share some of these while walking through how governments are building their own data products using open data as well as empowering civic hackers. I'll also walk through why data science at the government level is fundamentally different than data science in the private sector.

How to Avoid Pitfalls in Big Data Analytics Webinar

Datameer

Big data analytics is revolutionizing the way businesses are collecting, storing, and more importantly, analyzing data. However, the adoption of a big data analytics solution has its share of failures and false starts. Watch this webinar to learn how to navigate the most common obstacles of big data analytics. Datameer and MapR have worked with customers to identify and solve the common pitfalls organizations face when deploying Hadoop-based analytics. In this webinar, we will show you how to: • Find the balance between infrastructure and business use cases • Overcome challenges of using multiple tools that address big data analytics • Leverage all your resources (data scientists, IT and analysts) most effectively

DataOps: Nine steps to transform your data science impact Strata London May 18

Harvinder Atwal

According to Forrester Research, only 22% of companies are currently seeing a significant return from data science expenditures. Most data science implementations are high-cost IT projects, local applications that are not built to scale for production workflows, or laptop decision support projects that never impact customers. Despite this high failure rate, we keep hearing the same mantra and solutions over and over again. Everybody talks about how to create models, but not many people talk about getting them into production where they can impact customers. Harvinder Atwal offers an entertaining and practical introduction to DataOps, a new and independent approach to delivering data science value at scale, used at companies like Facebook, Uber, LinkedIn, Twitter, and eBay. The key to adding value through DataOps is to adapt and borrow principles from Agile, Lean, and DevOps. However, DataOps is not just about shipping working machine learning models; it starts with better alignment of data science with the rest of the organization and its goals. Harvinder shares experience-based solutions for increasing your velocity of value creation, including Agile prioritization and collaboration, new operational processes for an end-to-end data lifecycle, developer principles for data scientists, cloud solution architectures to reduce data friction, self-service tools giving data scientists freedom from bottlenecks, and more. The DataOps methodology will enable you to eliminate daily barriers, putting your data scientists in control of delivering ever-faster cutting-edge innovation for your organization and customers.

Turning Petabytes of Data into Profit with Hadoop for the World’s Biggest Ret...

Cloudera, Inc.

PRGX is the world's leading provider of accounts payable audit services and works with leading global retailers. As new forms of data started to flow into their organizations, standard RDBMS systems were not allowing them to scale. Now, by using Talend with Cloudera Enterprise, they are able to acheive a 9-10x performance benefit in processing data, reduce errors, and now provide more innovative products and services to end customers. Watch this webinar to learn how PRGX worked with Cloudera and Talend to create a high-performance computing platform for data analytics and discovery that rapidly allows them to process, model, and serve massive amount of structured and unstructured data.

The Five Markers on Your Big Data Journey

Cloudera, Inc.

Cloudera Fast Forward Labs: Accelerate machine learning

Cloudera, Inc.

Machine learning and artificial intelligence can change the world. Diagnosing heart disease. Detecting fraud. Predicting insurance claims. Revolutionizing agriculture. In business, machine learning and artificial intelligence drive new sources of revenue and lower costs. But executives struggle to define an investment strategy. Researchers introduce innovations in machine learning daily. Technical jargon is opaque. Vendor hype muddies the waters. Industry analysts cover the field, but only at a high level. Cloudera Fast Forward Labs accelerates your machine learning journey. We deliver a unique blend of applied research and hands-on explanations that you can apply to your business today. In this webinar you will: Meet the Cloudera Fast Forward Labs team Cut through machine learning hype Explore recent examples of applied research See exciting new ML techniques Hear how machine learning is delivering real business value on multiple use cases 3 things to learn: Explore recent examples of applied research See exciting new ML techniques Hear how machine learning is delivering real business value on multiple use cases

The Big Picture: Real-time Data is Defining Intelligent Offers

Cloudera, Inc.

New research shows that 57% of the buying cycle is completed before a prospect even speaks to a company. Marketers already know this, Ninety-six percent (96%) of organizations believe that email personalization can improve email marketing performance. But where do we get this increasingly personal direction? The answer is likely in your customer data. In order to understand your customer needs contextualized in the moment they feel the need to act you will require a platform that can leverage real-time data. Apache Kudu is a Cloudera component that makes dealing with quickly changing data fast and easy. Companies are leveraging next generation data stores like Kudu to build data applications that deliver smart promotions, real-time offers, and personalized marketing. Join us as we discuss modern approaches to real-time application development and highlight key Cloudera use cases being powered by Cloudera’s operational database.

DataOps - Big Data and AI World London - March 2020 - Harvinder Atwal

Harvinder Atwal

Title DataOps, the secret weapon for delivering AI, data science, and business intelligence value at speed. Synopsis ● According to recent research, just 7.3% of organisations say the state of their data and analytics is excellent, and only 22% of companies are currently seeing a significant return from data science expenditure. ● Poor returns on data & analytics investment are often the result of applying 20th-century thinking to 21st-century challenges and opportunities. ● Modern data science and analytics require secure, efficient processes to turn raw data from multiple sources and in numerous formats into useful inputs to a data product. ● Developing, orchestrating and iterating modern data pipelines is an extremely complex process requiring multiple technologies and skills. ● Other domains have to successfully overcome the challenge of delivering high-quality products at speed in complex environments. DataOps applies proven agile principles, lean thinking and DevOps practices to the development of data products. ● A DataOps approach aligns data producers, analytical data consumers, processes and technology with the rest of the organisation and its goals.

Intuit's Data Mesh - Data Mesh Leaning Community meetup 5.13.2021

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Informatica Becomes Part of the Business Data Lake Ecosystem

Capgemini

Informatica is now part of the Business Data Lake ecosystem developed by Capgemini and Pivotal. Customers worldwide will now be able to leverage Informatica’s data integration software in addition to Pivotal’s advanced big data, analytics and application software, and Capgemini’s industry and implementation expertise. Informatica will deliver certified technologies for Data Integration, Data Quality and Master Data Management (MDM) to help enterprises distill raw data into actionable insights. http://www.capgemini.com/resources/the-business-data-lake-delivering-the-speed-and-accuracy-to-solve-your-big-data-problems

Data Science in Enterprise

Josh Yeh

Traditional BI vs. Business Data Lake – A Comparison

Capgemini

Traditional Business Intelligence (BI) systems provide various levels and kinds of analyses on structured data but they are not designed to handle unstructured data. For these systems Big Data brings big problems because the data that flows in may be either structured or unstructured. That makes them hugely limited when it comes to delivering Big Data benefits. The way forward is a complete rethink of the way we use BI - in terms of how the data is ingested, stored and analyzed. More information: http://www.capgemini.com/big-data-analytics/pivotal

Big Data LDN 2017: The 3rd Wave of Business Intelligence

Matt Stubbs

Making Hadoop based analytics simple for everyone to use

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Understand Your Customer Buying Journey with Big Data

Datameer

Imagine being able to use insights about your customer acquisition journey to design campaigns that improve conversion rates. What if you could identify points of failure along the customer acquisition path or during product usage? Today more than ever the role of the marketing and product executives have become data-driven. Business executives who leverage data to understand prospect and customer behavior have gained an edge over their peers. Big Data analytics is the key to unlocking insights from your customer behavior data and empowers you to combine and analyze all of your customer interaction data to drive customer acquisition and loyalty.

Financial Data Analytics with Hadoop

Chicago Hadoop Users Group

Adam Gugliciello, a 15-year veteran in Software Engineering and Systems Architecture specializes in highly available, parallel systems. In this session, we will answer common questions and demonstrate use cases on how Hadoop and Datameer help with asset management and risk management, fraud detection and data security. This presentation was given on January 24th at the CME Group's offices in Chicago, IL.

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Extending BI with Big Data Analytics

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MapR Technologies

Digital Government: Data + Government Isn't Enough | Wrangle Conference 2017

Cloudera, Inc.

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Datameer

DataOps: Nine steps to transform your data science impact Strata London May 18

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Intuit's Data Mesh - Data Mesh Leaning Community meetup 5.13.2021

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Informatica Becomes Part of the Business Data Lake Ecosystem

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Learn how organisations are able to drive better business outcomes from big data products and in turn, deliver personalised, real-time experiences to customers. We will walk through a common customer journey and demonstrate how to quickly test ideas and gather insights from data lakes, data pipelines, and sandboxes. See how to serve the needs of your business users, business analysts, and data scientists using AWS services for analytics, Big Data, and Machine Learning. Speaker: Vicky Falconer, Business Development Manager - Big Data, AWS

Better Business From Exploring Ideas - AWS Summit Sydney 2018

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Better Business from Exploring Ideas - Modern Data Architectures on AWS In this session you will learn how organisations are able to drive better business outcomes from products and deliver more personalised and real-time experiences to customers. We will walk through a common customer journey that shows how to quickly test ideas and get insights, built on top of data lakes, data pipelines, and sandboxes using the same platform advantages of Modern Data Architectures on AWS as some of our most prominent customers. See how to serve the needs of your business users, business analysts, and data scientists using AWS services for analytics, Big Data, and Machine Learning. Craig Stires, APAC Head of Analytics, Big Data, and AI, Amazon Web Services

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How to do Data Science Without the Scientist

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http://www.datameer.com With data scientists in short supply, it’s surprising that much of their precious time is spent doing ”data plumbing”—preparing data or servicing business users rather than doing actual data science. Hadoop and self-service Smart Analytics is changing this reality. Join Matt Schumpert, Director of Solution Engineering at Datameer, as he walks through a real-world use case and discusses the evolution toward self-service data science, freeing data scientists to the hard work we so badly need.

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The Economics of SQL on Hadoop

Datameer

Watch the recorded event at: http://info.datameer.com/Slideshare- Economics-SQL-Hadoop.html As organizations clamor to utilize their new investments in Hadoop ecosystems AND leverage their existing analytical infrastructures, many rush to integrate SQL as a data access layer to leverage existing skill sets and get started faster. However, this approach relegates Hadoop to a data management and processing platform rather than the storage and compute engine optimized for analytical workloads it was purpose-built to be. These slides by EMA and Datameer, will discuss the technical limitations of SQL on Hadoop and propose alternative ways to fully maximize Hadoop investments. You will understanding: *how SQL negates the inherent benefits of Hadoop *why technological paradigm changes can sometimes be good *use cases when SQL on Hadoop makes sense

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Understanding Customer Buying Journey with Big Data

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Big Data enables you to combine the vast amount of customer behavior data being generated from mobile, web, social media, transaction systems, Ads and turn them into new insights that drive customer acquisition and retention. This talk will highlight and showcase how leading edge companies are leveraging big data to: Combine customer interaction data to understand customer buying journey Understand high-value customer behavior beyond profile segmentation Identify the most common path to customer churn Perform market basket analysis to help with cross-sell and up-sell Speakers: Matt Schumpert Director of Product Management Matt has been working in the enterprise infrastructure software space for 15 years in various capacities, including product management, sales engineering, sales leadership and strategic alliances. An early employee of Big Data pioneer Datameer, Matt is currently focused on driving the strategic direction and technology strategy for Datameer’s flagship Big Data analytics product. Previously, Matt built the sales engineering organization at Datameer, managed strategic partnerships at Oracle & BEA Systems in the US an Europe, and drove sales of business rules management software at ILOG (now IBM). Matt holds a BS in Computer Science from the University of Virginia.

Transform Banking with Big Data and Automated Machine Learning 9.12.17

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Banks are rich in valuable data and can build and maintain a competitive advantage by identifying and executing on high-value machine learning projects leveraging the rich data available.This webinar will describe use cases fit for big data and machine learning in the banking sector (commercial, consumer, regulatory, and markets) and the impact they can have for your organization. 3 things to learn: * How to create a next generation data platform and why it is important * How to monetize big data using predictive modeling and machine learning * What is needed for automated machine learning as a sustainable, cost-effective, and efficient solution

Why big data matters to case management

mister_moun

EIS-Webinar-MDM-Personalization-2023-03-15.pdf

Earley Information Science

The Increasing Criticality of MDM for Personalization for Customers and Employees Master data management seems to be one of those perennial, evergreen programs that organizations continue to struggle with. Every couple of years people say, “we're going to get a handle on our master data” and then spend hundreds of thousands to millions and tens of millions of dollars working toward a solution. The challenge is that many of these solutions are not really getting to the root cause of the problem. They start with technology and begin by looking at specific data elements rather than looking at the business concepts that are important to the organization. MDM programs are also difficult to anchor on a specific business value proposition such as improving the top line. Many initiatives are so deep in the weeds and so far upstream that executives lose interest and they lose faith in the business value that the project promises. Meanwhile frustrated data analysts, data architects and technology organizations feel cut off at the knees because they can't get the funding, support and attention that they need to be successful. We've seen this time after time and until senior executives recognize the value and envision where the organization can go with control over its data across domains, this will continue to happen over and over again. Executives all nod their heads and say “Yes! Data is important, really important!” But when they see the price tag they say, “Whoa hold on there, it's not that important”. Well, actually, it is that important. We can't forget that under all of the systems, processes and shiny new technologies such as artificial intelligence and machine learning lies data. And that data is more important than the algorithm. If you have bad data your AI is not going to be able to fix it. Yes there are data remediation applications and there are mechanisms to harmonize or normalize certain data elements. But looking at this holistically requires human judgment: understanding business processes, understanding data flows, understanding dependencies and understanding of the entire customer experience ecosystem and the role of upstream tools, technologies and processes that enable that customer experience. Until we take that holistic approach and connect it to business value these things are not going to get the time, attention and resources that they need. Seth Earley, Founder & CEO, Earley Information Science Dan O'Connor, Senior Product Manager at inriver

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Remediate Tech Debt or Drive Innovation - AWS Summit Sydney 2018

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1. Easier, Faster, Smarter

2. View Recording !! ! You can view the recording of this webinar at:! ! http://info.datameer.com/Online-SlideshareCustomer-Case-Studies-Big-Data-Analytics.html! © 2013 Datameer, Inc. All rights reserved.

6. Legacy Modernization! Traditional EDW! 18mo! $1M+! $1M! Datameer on Hadoop! 12 wk! 3mo! Time to Cost Per ! Salaries Time to Build! 100TB! Required! Insights! © 2013 Datameer, Inc. All rights reserved. Time to Build! $400k! $133k! 2d! Cost Per 100TB! Salaries Required! Time to Insights!

16. Predictive Support! é Proactive Customer Support Component Planning Logs Services Id’d Product Issues Network Data Development Unstructured Logs Accurate Forecasting 111001 110010 01101001 01100100 10011101 01101110 Sales © 2013 Datameer, Inc. All rights reserved.

20. @Datameer!

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