BIG DATA IN BUSINESS

Is it a real need or just trendy? Why does it apply to my case?

Big Data

Petabytes: Google 300 PB, facebook: 45 PB, Yahoo! 180 PB Exabytes: U.S. healthcare Zetabytes: 2011, 1.8 ZB created. World Information 9.57 ZB YottaByte, Brontobyte, GeopByte to be reached

I do not have such a big volume of data A big European company = Terabytes

But could or will have it: Ever increasing amount of data, and more heterogeneous: Ubiquity, mobility, geolocation, social networks, internet, sensors, M2M CRMs, Call Centers, Emails, Documents, logs, voice…

"There were 5 exabytes of information created by the entire world between the dawn of civilization and 2003. Now that same amount is created every two days."

Google Ceo Eric Schmidt

Unstructured or semi structured data, equal to 85% of available data, is not used by companies

This represent the new Fuel for companies

83% of the surveyed companies were able to do things with Big Data that seemed impossible to achieve before

“The art of possible” “Impossible is not a fact, it’s an opinion”

Value and real ROI are the best KPIs

•Increase of client acquisitions

• Resource optimization

• Increase in sales

• Customer loyalty

You can’t stay stuck in old paradigms

When to use it?

Extract value from data in any point of their life cycle

• Past: Stored data, Batch mode

• Present: Current data flows, Real time

• Future: Data and future actions, Predictive

Big volume of data

Get value from Unstructured data

Get value from external data

Need for time or cost processsing reduction

Need for Data streaming analysis in real time

Algorithms, prediction or interactive analysis

Transform data into insights and value

Transformation to a Data driven company

Customer Pain

“I know I have to change to Big Data but…”

How do I start to use with? When?

Which technology?

How do I acquire the knowledge?

How to use it?

Iterative and Cyclical Choose a particular use case with a clear ROI and time and budget limits

vs Big Bang Avoid building a Big Data generic system and then implementing projects over them

Which Technology?

Bigtable

From Big Data 1.0 To Big Data 2.0

Big query F1

12 YEARS GAP

A Technological Change

∙ Up to 100x faster than Big Data 1.0

∙ Interactive analysis

∙ NoSQL with SQL Interface

∙ No need to change previous way of work

CUSTOMER SOLUTION

Big Data 2.0

Cloudera CDH4* Hortonworks HDP*

EMC Greenplum Datastax Platform EMC Pivotal HD Microsoft HDInsight

MapR M3-M5-M7 Hadapt platform IBM Inphosphere Biginsight Intel Hadoop

Open Source Closed Closed based on Open Source

Which technology?

Cloudera Impala Hortonworks Stinger MapR Apache Drill Google Big Query Amazon EMR _& Red shift BIG DATA 2.0

BIG DATA 1.0

Stratio

NoSQL C-Store Basho Riak VMWare Redis Mencache

Apache HBASE

Apache Cassandra

Apache CouchDB

VoltDB Voldemort Espresso

HP Vertica

Apache Flume Apache S4 Aurora Kafka Storm Scribe Stream Processing

StreamBase Platform

IBM Inphosphere Streams Hstreaming Platform EsperTech ESPER SQLStream Platform

Graph database NEO Techonology Neo4j* Apache Giraph FlockDB

Almacenamiento Cassandra FS Apache HDFS EMC Isilon OnFS

Batch of new technologies that allow us to extract value out of a dataset which, due

to it’s volume, variety or velocity, was not previously exploited

From Big Data 1.0

“Set of new technologies that extract value from all the available data of a

company”

To Big Data 2.0

Use Cases

The Bubble filter

You must enter in the user bubble

Description: Recommendation Engine based not only in the purchase history of the customer, but also in their navigation

Advantages:

Increase in clickthrough

Increasing Conversions

Increase in sales

Antena 3, nubeox : Big Data Recommendation engine Monitoring of Streaming Videos

+160% clicks vs. one size fits all

+79% clicks vs. randomly selected

+43% clicks vs. editor selected

Recommended links News Interests Top Searches

Description: Customizing homepages based on user navigation

Analysis and customization of the homepage and site in real time for each user based on their browsing

Modification of contents, highlights, ads, in real time based on user history

Advantages: Over 300% increase in clickthrough

Creating millions of web pages in real time

Increasing Conversions

Increase in sales

Cost ten times lower than other solutions

Customizing Web Sites: Behavioural Customization

Description: Newsletter development, email-marketing or any other sent material segmented by individual preferences Analyzes and takes into account: • Financial information and user data • Navigation and usage information from previous

marketing shipments • Mobile app data (GPS, payments, browsing of

offers…) • Users’ information from the social networks

Advantages: Increased clickthrough

Increase in conversions and sales

Natural language processing – semantics and sentiments

Combines private and public data

Personalized Marketing with DataShake integration

Description:

Complementing the internal data of a company by combining the structured and the unstructured data, with the data generated by the web and social networks, allows us to determine the validity of the data of our brand, product or company.

The comparison and analysis of internal and external data (web) increases the value of our data and allows us to gain a competitive advantage over our competitors.

Advantages: It allows sales improvement.

Improves loyalty.

Increases Conversions.

Detects errors or data manipulation.

SEO improvement with regards to the users and the public data.

Improves marketing and product boosting with regards to trends.

Complement private structured data with unstructured and public data

Page 32 Big Data

Description: Creation and/or complementation of BI systems and data analytics

ETL tools and data uploading with a much higher volume than the traditional ones

Capacity for analysis and visualization of all types of data, including graphs and new data types

Advantages:

Ability to work with larger datasets without the need to add or delete

Much faster and reliable systems

Massive reduction in cost (M € versus k €)

Natural language processing – semantics and sentiments

A possibility to combine internal data with external data (private and public data)

BI and data analytics

Description:

Collect mobile data, anonymised and aggregated, to understand how segments of the population collectively behave. Trace trends and the behaviours of crowds, not individuals. Use this insight to enlighten the space between organisations and their users, enabling them to improve their propositions, and businesses.

Focus: By being able to measure real behaviour, in near real-time, 24/7, 365 days a year, we can show the actual impact on society, therefore enabling businesses and local government to make better decisions.

Telefónica Dynamic Insights (Smart Steps)

Description: Analysis of large volumes of data, logs, security systems, transactional systems

Faster correlation mechanisms and machine learning algorithms allow early detection of attacks and security risks with extra care to false positives

Internal fraud detection analyzing data and events from applications and risk operations

Advantages:

Combines data from transactional systems with the SIEM to help fight fraud

Tracks and identifies new fraud methods and trends via user reviews

Fraud detection techniques specified through the use of built-in patterns

Much larger data volumes and much higher velocity

Combines private and public data

Security and fraud detection

Description: The Remote Maintenance & Monitoring System (RMMS), provide a powerful, scalable and flexible SCADA system to perform and wide range of tasks required by CNS agents such as maintenance, supervision, configuration and operation.

Integration of different systems and equipment shall be possible and straightforward using open standard protocols, real time monitoring, data storage, testing, reporting, events notification,…

Focus:

The main task of the RMMS is to provide complete access to the equipment supervised in order to monitor every single available parameter as a mean of avoiding personnel mobilization to the remote location. Different levels of control over the system are also provided to cover the requirements of supervision, maintenance and control. Five main elements compose the RMM system: • RCSU: Remote Control and Status Unit. • TP: Tower Panel. • RMM: Remote Management & Monitoring. • LMT/RMT: Local / Remote Management Terminal. • CMMS: Central Management & Monitoring System.

M2M IoT: PARK AIR SYSTEMS NORWAY (RMMS)

Description: Big Data Search Assist: Search engines optimized for Big Data with self-learning improvements based on use

Search engines for websites, intranets, apps

With instant real-time search, single box with natural language processing, suggestions, highlighting, automatic corrections, “you wanted to say” tips, etc ...

Advantages:

Easy management for business users: Order of results, filters, etc ...

Advanced features of the search engines with a cost ten times lower than other solutions

Improved performance and scalability compared to other solutions

Easy to integrate and use

Search Engines

Description: It gives a full 360 º of a company or brand online, showing a tool that integrates the three aspects that define your actual online image: How am I doing on social networks?: Do I know how to usevfacebook, twitter, google +, youtube, linkedin? How many followers do you have, are you an influencer, do you generate content that spreads out? What is my presence and reputation on the Internet: When it comes to me, how do people talk about me, what is said, how does it evolve over time, what is my position on the Internet regarding my competitors in the different aspects that interest me. SEO: Simple and practical analysis of both internal SEO and external SEO to complement and give an integrated view of the above aspects of reputation and social dialogue.

Advantages: Real improvement of the company or the product by analysing the evolution over time of the three major aspects that define your online reputation. It improves the negative aspects, and reinforce the positive ones. Increase in sales: Helps optimize and follow marketing campaigns and improve sales. Improving conversions and attracting new customers.

ORM and social dialogue

Description: Analyzing various social networks and movements, looking for brand penetration, identifying influencers in conversations and a static map of associated terms. Advantages: Entering the social dialogue and hot topics at the right time multiplies by 100 times the viralization

View how a social network moves as time goes by

Allows to know what that the user is talking about when referring to my products or my brand.

Detection of influencers and detractors

Optimal visualization of the information.

Identification of the tags used most frequently by the network to improve your SEO.

Social Mining

Description: Search the social network comments and mentions of interest of a particular issue or event for further evaluation, influencers detection and graphical display of the conversation to facilitate analysis. Advantages: Show real-time event (symposium, forum, seminar, etc..) with visual information.

Get opinions and feelings about a topic in social networks in real time

Identify the influencers of a hot topic

Risk detection and prevention

Emotional mining: Know the term that is most popular for some people, brand, event, etc.and this way you can know about the generated feelings by the most important terms.

Social Network Tracking

Description: Search the network content and publications on specific subjects of our interest, to detect, filter, collect and process relevant information in semi-real time or batch. Associated with the semantic analysis this allows the detection and classification of the contents effectively. Advantages: Allows the generating of sites in a dynamic way without any intervention or exhaustive searches, with the contents collected and categorized.

Unifies in a single web all the tasks that users have to do manually, so it saves them money and generates loyalty.

Web Content Scraping

Description:

Monitoring the download and streamming of videos.

Analysis of streaming

Quality of streaming

Peaks of service and bottle neck

Advantages:

Problems detection and alerts

Optimization of service

Tracking of campains

Tele5: Monitoring of logs for Streaming Videos

Description: Allows you to label and categorize automatically and massively, any type of content or information.

Advantages: Allows searching, categorization, clustering, and be able to extract value out of information otherwise hardly findable and usable. Utilizes state of the art tools to identify entities, NED systems, NERD. These tools combined with the use of disambiguation of entities using a Big Data system containing the Wikipedia and other sources of information. Speed processing capabilities and data volume superior to that of other systems.

Massive information tagging

SUMMARY

Is not about Big Data, is about getting maximum value from data:

Get all the value data can give Process and analyze new types of data: Unstructured, semi-structured, streams of data Convert data into big insights Become a Data driven company

“the best way to predict the future is to create it”

Ride The “Big Data” wave

Q&A