Posted By Oscar Padilla06/05/2013
I had a chance to attend the LiveRamp event last week in Palo Alto. It was phenomenal information-packed day. Naturally, LiveRamp is in the business of onboarding offline data and creating trackable cookies from your offline data. So a lot of the conversation was around data, and yes, the role of big data across the advertising world.
There were too many great panels to recap all of them, but this link to LiveRamp’s blogger Fahim Zaman does a nice job summarizing key speakers and areas covered.
A took away three key points that I see impacting our business and the advertising community:
The data transformation is happening. We’re seeing how data is creating a new advertising environment that is demanding much richer insights into your potential audience. And big data is allowing companies to from unusual customer touch points.
Charlie Stryker of Venture Development Center cited a good example of this with Disney. Disney mines and interrogates every school calendar to understand when schools are closed and identify opportunities to push communications to parents based on these school closed dates. They scrub data from over 40,000 schools schedules across the country through a combination of manual and automate procedures to collect this powerful data asset.
Effective attribution is difficult due to Fragmented channel “ownership”. Presently, client advertising is highly fragmented where brands manage advertising budgets based on specific channels. In other words, online advertising budgets are controlled by one group; television by another group, and mobile advertising by yet another group. Analytics and metrics from these different groups are often collected and managed in silos. But, this is not how consumer behaves. Consumers don’t have neatly compartmentalized channel consumption behaviors. We consume media across all channels and screens simultaneously and seamlesly. Advertisers need to make media buying decision played off on how consumers actually interact with media devices, not how they internally operate.
A post cookie era is coming. There were extensive conversations on the future of cookie data as a unique identifier. Given how consumer behaves across multiple devices and screens, cookies are not the most effective ad tracking approach. As alternatives, panelist talked about the upside and challenges of using an IP identifier. But this posses a big problem in Europe where due to PII regulations, IP data cannot be used for ad tracking purposes and therefore limiting the use of IP as a global solution. Several start-up companies are already experimenting with “Fingerprinting”, where you track the devices themselves rather than the cookies placed on them. The technology applies to desktop computers, tablet devices, and potentially any device with a data connection.
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Posted By Oscar Padilla05/17/2013
Today Tableau Software went public with a highly successful IPO with its shares skyrocketing to nearly 60%. Tableau is a critical component to a Big Data offering. They make possible the reporting and data visualization of complex data models through an intuitive drag-and-drop user interface. What’s particularly attractive of Tableau is that it’s design around both technical and non-technical user.
What really got me excited about today’s Tableau’s successfully IPO announcement is that this is the first Big Data company IPO that is generating much needed visibility of Big Data beyond just a buzz word of the day (actually, to be fully accurate I think the first IPO in the Big Data space was Splunk that went public last year).
Naturally, all of us at Luminar welcome this exposure as we built an advanced analytics solution, to understanding and model Hispanic-purchasing behaviors, based on a Big Data environment. But what’s compelling about big data now is not that big data itself is a new phenomenon.
As a Forbes writer pointed out in a recent article, analyzing large complex data sets has been going on for years in many industries (airlines, financial institutions, retailing, etc).
What’s different today is the underlying technology that makes processing this vast amount of data significantly more efficient and accessible to a much broader user base – from large Fortune 500 enterprises to small start-ups.
Tableau definitely commands a huge presence in the Big Data space and this IPO is truly paving the way in accelerating the understanding of a data-driven word with so many applications where we’re just starting to scratch the surface on what’s possible.
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Posted By Oscar Padilla05/06/2013
I recently read a post on Brian Solis blog titled “Without Analytics, Big Data is Just Noise”. This could not be closer from the truth. We all know there’s a lot chatter on Big Data and the three “V” (volume, velocity variety) associated with its definition; but at the heart of big data, is the ability to carry out highly complex analytics of desperate data sources. Big Data on itself doesn’t provide the value, the key is to couple Big Data with advanced analytics in order generate valuable insights.
For example, we’re working on a particular financial application where we’re ingesting national sales data from multiple sources as well as other non-financial data streams. The challenge is not related to the volume or size of the data, but more so to the time it takes to produce the reports needed. This is mainly due to the fact of having to do multiple passes on the data running complex algorithms. Although Bid Data is playing an important role in collecting, storing and deciphering the data; the challenge though is more related to having a high-performance analytics environment that can reduce latency and drastically cut reporting times.
That’s why I like the term Big Data Analytics because that’s really what it is. What does matter that we can accumulate hundreds of Terabytes of data if you can’t analyze it fast enough to act on it or make timely decisions?
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Posted By Esteban Lopez Blanco05/04/2013
The Data Deluge… Sounds Familiar?
Lots of variables. Little time. Lots of pressure – What variables really matter? What does it mean? Are there outliers? What to do with correlated inputs? How much do I know about my problem? What exactly don’t I know about the problem? How to change it? Can I trust my conclusions? —These questions are raised in almost any data-driven project.
I like to summarize everything with a graphic that at Luminar we call the Big Data Arrow:
Are you sure your company has the right infrastructure, resources to address everything above, from Data to Actions?
When thinking about growth strategies there are two big tidal waves compounding you want to surf :
- The “New Baby Boomers” = US Latinos.
- The exponential growth of Data = Big Data
If you got here, keep reading. At the end you will find the latest Economist Intelligence Unit Report: The Data Directive.
In much the same way that the Internet was the fundamental disruptive technology in the 1990s, today the myriad forms of data emerging from our Internet-enabled digital world added to the offline world transactions data, promise a similar transformation. But how far has the data-driven revolution gone? The latest EIU report explores to what extent the ongoing data revolution is delivering real change within businesses.
Here you have our Top 10 Summary:
- There is a clear correlation between high-growth companies and use of data.
- Undoubtedly key to their success is the fact they have done more to reorganise their structures and leadership around data and to introduce data-management strategies.
- High-growth firms make better use of their data
- While no-growth firms worry about the unknown, high-growth firms worry about how to resource their data plans
- High-growth firms more often have a solid data management strategy in place
- All C-suite functions are finding uses for data, but so far data has proved most valuable for marketing leaders
- Many companies are unsure about the extent of data-fueled strategic transformation within their business
- Working out which data matters most is the top challenge for firms, but there are wide ranging issues to overcome
- Those companies that claim to be best at extracting insights from data are not necessarily looking to their CIOs to lead on this initiative
- Luminar can help…
Here the link to the full report, enjoy! The Data Directive EIU
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Posted By Esteban Lopez Blanco04/24/2013
If you are here, you might be a big data enthusiast. Or you might be looking to understand more about Luminar services. Let me tell you this. Best practices for big data are about creating value for your company by delivering better and faster insights by answering questions that you could not answer before. Or better yet, being able to formulate new questions while knowing you now have the power to find the answers. This is the first of a series of brief posts. Our intention is to help you understand what is big data, and helping you to assess if your company is big data ready. In other words, help you to prepare your company to build value and drive efficiencies to build growth and value.
Let’s start by defining what is data and what is big data.
The terms data, information and knowledge are frequently used for overlapping concepts. The main difference is in the level of abstraction being considered. Data is the lowest level of abstraction, information is the next level, and finally, knowledge is the highest level among all three. Data on its own carries no meaning. For data to become information, it must be interpreted and take on a meaning.
What is big data?
Big data has three attributes: volume, velocity and variety. We know we are dealing with big data when one of this three attributes are a challenge to extract value. Then big data is a series of processes and tools to deal with big amounts of data, that are produced fast, sometimes in real-time and from many different sources and structures.
I leave with you the following graphic to get you thinking on process and tools that we will review on our next post.
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Posted By Oscar Padilla10/31/2012
Last week’s event brought together decision makers using the raw power of big data to drive business strategy, as well as the practitioners who collect and analyze the data. As the O’Reilly organizers said, the focus was on forward-looking insights and ahead-of-the-curve thinking. Since many weren’t able to attend the entire event, here’s an Executive Summary with five key insights from the Strata Conference.
1) Continued need to understand the basics
Our presentation at Strata/Hadoop was “how a traditional media company embraced big data” where we basically provided a case study on how our company implemented a big data platform. By the crowd of 300+ attendees, it was clear that understanding how Big Data is implemented is still a challenge for many companies, and I’m not just referring to technology alone. Many of the post presentation questions were regarding how we build a business case, understanding ROI, data licensing concerns, and other business questions that supported the implementation of a big data environment.
2) Shortage of professionals
This was a common thread throughout the entire conference. The shortage of Big Data professionals is occurring across all aspects of the Big Data environment; but more specifically, the highest shortage is for Data Scientists. Several universities across the country are starting programs to address this labor shortage but it will be a hard task to fill these jobs. Based on a study conducted by D&B and McKinsey Global Institute, by the year 2018, the gap of professionals will reach nearly 200,000 graduates.
3) “Enterprise-ifcation” of Hadoop
It was apparent at the conference that there is greater integration occurring across all major Big Data players making Hadoop much more adaptable to the corporate enterprise environment. By more closely integrating Business Intelligence, analytics, security products, and data with existing IT and data centers solutions Hadoop is becoming much more rapidly adaptable to corporate America.
4) Validation of our Big Data technology solution
Our platform continues to be confirmed – Talend, Hadoop, Pig, Hive, Scoop, HBase R, Tableau. We spend significant time and effort designing a Big Data environment that would support our technology goals and provide the needed platform to offer the right solutions to our clients. Based on our discussion with vendors and colleagues participating in various technology presentations, we feel more confident than ever that we put in place a best-of-breed technology platform to support our growth.
5) Expanded use of big data and visualization
A big component of Strata this year was data visualization and how different tools are being used to present analysis in much more rich and compelling ways – there were 14 different sessions just on data visualization. At the end of the day, these tools that effectively present data are ultimately what your customer will experience from a big data solution. A number of companies illustrated how they turned complex data into easily understood and interactive insightful information. There were also great discussion panels around best practices and effective “story telling” through data methods.
A “bonus” key takeaway is the energetic and optimistic mood of all who attended the event. There’s a big reason to be confident in the essential nature of big data in our economy: it’s estimated that by 2018, our industry is poised to achieve and drive additional complementary businesses that will equal $230 billion. That’s probably the reason that attendance grew from 600 attendees in 2011 to 3000 participants last week. As they said during the show, the future belongs to those who understand how to collect and use their data successfully. See you next year – we’ll definitely be there!
Posted In: Blog
Posted By Oscar Padilla10/26/2012
The O’Reilly Strata + Hadoop World conference was extremely successful. We’re energized by the thought leaders, industry colleagues and clients who were there – we had a full-house with over 300 attendees. One key partner we want to acknowledge is Impetus Technologies, a leading provider of Big Data Analytics. We delivered a presentation together yesterday, How a Traditional Media Company Embraced Big Data that got a lot of people talking. In addition, Impetus distributed a press release announcing our partnership.
Another important partner supporting us at the event was Hortonworks. Instrumental in implementing Luminar’s Big Data environment, Hortonworks built the framework powering the terabytes of data Luminar’s data scientists analyze each day.
Needless to say, we’re excited about our partnerships and look forward to future announcements about the ways we’re supporting our clients’ success.
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Posted By Oscar Padilla10/23/2012
We love New York and O’Reilly’s Strata + Hadoop World conference! We’re meeting industry movers and shakers and learning about the power of big data to drive business strategy. Also, we’re gearing up for our presentation on Wednesday, Oct. 24, How a Traditional Media Company Embraced Big Data. During the session, we’ll review five lessons learned in the launch of Luminar as Entravision’s data-driven services division. On Thursday, Oct. 25, I’m hosting a 1-hour Q&A session certain to be a lively discussion on big data strategy. See you there! During Strata, we’ll be gathering insights and compiling them into a top five list of things you should know – key findings about big data. Be sure to check back to learn more.
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Posted By Oscar Padilla10/12/2012
I recently learned about this project (The Human Face of Big Data) through a colleague from our parent company Entravision. It’s a fascinating project on big data, but it’s not what you would typically associate Big Data with. Once you download the application to your smartphone (iPhone or Android), you’ll be asked a series of questions and the information you provide is mapped instantly against a worldwide data pool of other users.
This is an example on how big data is being used to manage vast amount information, but more importantly, how Rick Smolan, the photographer behind this project (with the help from EMC2) has managed to take the concept of Big Data to the masses to interact with. What I like about this project is that in a very simplistic way – the application’s UI is beautifully designed and I could write an entire post just on the UI of this app – it begins to demystify how big data is being used. Big Data is not just a tool that we use in marketing to conduct complex modeling and analytical insights; but it’s also a tool that helps us with every day life. In a review that Wired Magazine wrote about this project, the author quotes how “The world changed because of the Internet, and the world will change because of big data,”. This could not be a more accurate statement. I think we’re just starting to scratch the surface on what’s possible and what’s to come.
Tags: Big Data
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Posted By Oscar Padilla09/27/2012
Last week I read an eMarketer article that cited that “less than one in five retail executives was unaware of Big Data.” I felt this was not so much an insight about the lack of knowledge of Big Data, but more so that the retail space is leaving money on the table. I’m continually seeing retailers at a loss when it comes to big data and the value it brings to retail. Only about 11.7% of retailers consider themselves “big data evangelists.” Given the size of retail industry, this has significant financial implications — the majority of retailers simply are not maximizing the revenue potential from their audience.
One would think all retailers would be big data evangelists, as they have access to so much transactional data that they would have the greatest knowledge and potential. Yet they’re anything but, according to a recent study from Edgell Knowledge Network. (show chart) The idea of cross-pollinating data, pulling all the structured and non-structured data together to gain insights, is only just beginning to make its way into the retailer strategy.
Here’s why it should be part of every retailer strategy: through sophisticated technology and analysis, big data reveals in-depth shopper profiles — who your customer is, what he or she is buying from you and your competitors, how much was spent. It helps retailers deliver precise messaging and feeds right into the concept of developing customer lifetime value.
I recall when eCommerce came onto the scene, it was not readily embraced by retailers As the numbers bear out, such is the case with big data. With time and education, retailers will soon capitalize on big data and become “big data evangelists” across the board.
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