Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.

This week on Making Data Simple, we have Oliver Claude Portfolio Offering Manager for Data and AI and Oliver is a Data Governance expert. Oliver also worked as a Chief Marketing Officer, VP and Chief Solution Owner, Solution Management, and Consulting, Al and Oliver discuss Data Governance and Data Ops and how it all fits into your business. 

Show Notes 2:50 - What is the definition of Data Governance? 4:06 - What is Data Ops? 4:40 - What is IBM doing with Data Ops? 5:16 - How have we automated our tools? 6:58 - What is better red or white wine? 7:33 - What is the future of Data Governance? 9:37 - How is Data Governance and Data Ops related to AI? 11:06 - What are the pitfalls for customers implementing Data Governance? 12:10 - How do companies get started? Oliver Claude - LinkedIn IBM DataOps    Connect with the Team Producer Kate Brown - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Do you want to create data analysis reports without writing a line of code? This book introduces SAS Studio, a free data science web browser-based product for educational and non-commercial purposes. The power of SAS Studio comes from its visual point-and-click user interface that generates SAS code. It is easier to learn SAS Studio than to learn R and Python to accomplish data cleaning, statistics, and visualization tasks. The book includes a case study about analyzing the data required for predicting the results of presidential elections in the state of Maine for 2016 and 2020. In addition to the presidential elections, the book provides real-life examples including analyzing stocks, oil and gold prices, crime, marketing, and healthcare. You will see data science in action and how easy it is to perform complicated tasks and visualizations in SAS Studio.You will learn, step-by-step, how to do visualizations, including maps. In most cases, you will not need a line of code as you work with the SAS Studio graphical user interface. The book includes explanations of the code that SAS Studio generates automatically. You will learn how to edit this code to perform more complicated advanced tasks. The book introduces you to multiple SAS products such as SAS Viya, SAS Analytics, and SAS Visual Statistics. What You Will Learn Become familiar with SAS Studio IDE Understand essential visualizations Know the fundamental statistical analysis required in most data science and analytics reports Clean the most common data set problems Use linear progression for data prediction Write programs in SAS Get introduced to SAS-Viya, which is more potent than SAS studio Who This Book Is For A general audience of people who are new to data science, students, and data analysts and scientists who are experiencedbut new to SAS. No programming or in-depth statistics knowledge is needed.

Bernie Cho is a music executive with more than 21 years of culture creation in the Asian music, television, and pop culture industries. As President of DFSB Kollective, a Seoul-based independent artist and label services agency that specializes in providing digital media, marketing, and distribution solutions to 600+ Korean Pop music artists, DFSB collaborates with artists and their management to devise customized strategies that directly connect them to their local and global fans. Since 2009, the agency has successfully produced numerous K-Pop concerts/showcases around the world as well as secured No. 1 chart debuts for various K-Pop albums in North America, East Asia, Western Europe, and Australia.

As one of the first and foremost K-Pop music exporters, DFSB Kollective and its artists have been featured speakers/performers at top international music industry events (CMJ, CMW, SXSW, Coachella, The Great Escape, Glastonbury, Summer Sonic, Music Matters, MusicBiz, and MIDEM). Bernie himself has been involved with the startup of six TV channels, two concert series, and one film festival.

A true executive all-rounder, Bernie served as the Head of MTV Korea’s Digital Media Production team and worked for nearly two decades in the Korean music and TV industries as a Creative Planner, Program Producer, and Show Host. Though Bernie has no relation to Chartmetric’s CEO Sung Cho, Bernie is an Advisor for several US and Korean music tech startups, including Chartmetric.

You can listen to Part 1 of this two-part episode here. Connect With Ushttp://podcast.chartmetric.com/http://chartmetric.com/https://blog.chartmetric.comhttps://smarturl.it/chartmetric_social

Continuing its commitment to developing and delivering industry-leading storage technologies, IBM® introduces the IBM FlashSystem® solution that is powered by IBM Spectrum® Virtualize V8.3.1. This innovative storage offering delivers essential storage efficiency technologies and exceptional ease of use and performance, all integrated into a compact, modular design that is offered at a competitive, midrange price. The solution incorporates some of the top IBM technologies that are typically found only in enterprise-class storage systems, which raises the standard for storage efficiency in midrange disk systems. This cutting-edge storage system extends the comprehensive storage portfolio from IBM and can help change the way organizations address the ongoing information explosion. This IBM Redbooks® publication introduces the features and functions of an IBM Spectrum Virtualize V8.3.1 system through several examples. This book is aimed at pre-sales and post-sales technical support and marketing and storage administrators. It helps you understand the architecture, how to implement it, and how to take advantage of its industry-leading functions and features. Applicability: This edition applies to IBM Spectrum Virtualize V8.3.1 and the associated hardware and software that is detailed within. The screen captures included within this book might differ from the generally available (GA) version because parts of this book were written with pre-GA code. On 11 February 2020, IBM announced that it was simplifying its portfolio. This book was written by using previous models of the product line before the simplification; however, most of the general principles apply. If you are in any doubt as to their applicability, contact your local IBM representative. IBM Knowledge Center: In this book we provide links to Knowledge Center and a description of the relevant section that provides more information. Our starting point is the IBM FlashSystem 9200 family page, and the reader may have to select the product that applies to their environment.

Bernie Cho is a music executive with more than 21 years of culture creation in the Asian music, television, and pop culture industries. As President of DFSB Kollective, a Seoul-based independent artist & label services agency that specializes in providing digital media, marketing, and distribution solutions to 600+ Korean Pop music artists, DFSB collaborates with artists and their management to devise customized strategies that directly connect them to their local and global fans. Since 2009, the agency has successfully produced numerous K-Pop concerts/showcases around the world as well as secured No. 1 chart debuts for various K-Pop albums in North America, East Asia, Western Europe, and Australia.

As one of the first and foremost K-Pop music exporters, DFSB Kollective and its artists have been featured speakers/performers at top international music industry events (CMJ, CMW, SXSW, Coachella, The Great Escape, Glastonbury, Summer Sonic, Music Matters, MusicBiz, MIDEM). Bernie himself has been involved with the startup of 6 TV channels, 2 concert series, and 1 film festival.

A true executive all-rounder, Bernie served as the Head of MTV Korea’s Digital Media Production team and worked for nearly 2 decades in the Korean music & TV industries as a Creative Planner, Program Producer, and Show Host. He has earned a Bachelor’s degree from Dartmouth College in Government/Asian Studies; graduated from the UCLA Anderson - Executive Entertainment & Media Program, and even matriculated from the Foundation Film Program at Vancouver Film School.

Though Bernie has no relation to Chartmetric’s CEO Sung Cho, Bernie is an Advisor for several US & Korean music tech startups, which happens to include Chartmetric.

We’ve split this talk into two episodes for easier listening. Connect With Ushttp://podcast.chartmetric.com/http://chartmetric.com/https://blog.chartmetric.comhttps://smarturl.it/chartmetric_social

Once every four years in the United States, there is this thing called a "presidential election." It's a pretty boring affair, in that there is so much harmony amongst the electorate, and the two main candidates are pretty indistinguishable when it comes to their world views, policy ideas, and temperaments. But, despite the blandness of the contest, digging in to how the professionals go about forecasting the outcome is an intriguing topic. It turns out that forecasting, be it of the political or the marketing variety, is chock full of considerations like data quality, the quantification of uncertainty, and even () the opportunity to run simulations! On this episode, we sat down with G. Elliott Morris, creator of The Crosstab newsletter and a member of the political forecasting team for The Economist, to chat about the ins and outs of predicting the future with a limited set of historical data and a boatload of uncertainty. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Summary In order to scale the use of data across an organization there are a number of challenges related to discovery, governance, and integration that need to be solved. The key to those solutions is a robust and flexible metadata management system. LinkedIn has gone through several iterations on the most maintainable and scalable approach to metadata, leading them to their current work on DataHub. In this episode Mars Lan and Pardhu Gunnam explain how they designed the platform, how it integrates into their data platforms, and how it is being used to power data discovery and analytics at LinkedIn.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it? I’m working with O’Reilly on a project to collect the 97 things that every data engineer should know, and I need your help. Go to dataengineeringpodcast.com/97things to add your voice and share your hard-earned expertise. When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $60 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! If you’ve been exploring scalable, cost-effective and secure ways to collect and route data across your organization, RudderStack is the only solution that helps you turn your own warehouse into a state of the art customer data platform. Their mission is to empower data engineers to fully own their customer data infrastructure and easily push value to other parts of the organization, like marketing and product management. With their open-source foundation, fixed pricing, and unlimited volume, they are enterprise ready, but accessible to everyone. Go to dataengineeringpodcast.com/rudder to request a demo and get one free month of access to the hosted platform along with a free t-shirt. You listen to this show to learn and stay up to date with what’s happening in databases, streaming platforms, big data, and everything else you need to know about modern data platforms. For more opportunities to stay up to date, gain new skills, and learn from your peers there are a growing number of virtual events that you can attend from the comfort and safety of your home. Go to dataengineeringpodcast.com/conferences to check out the upcoming events being offered by our partners and get registered today! Your host is Tobias Macey and today I’m interviewing Pardhu Gunnam and Mars Lan about DataHub, LinkedIn’s metadata management and data catalog platform

Interview

Introduction How did you get involved in the area of data management? Can you start by giving an overview of what DataHub is and some of its back story?

What were you using at LinkedIn for metadata management prior to the introduction of DataHub? What was lacking in the previous solutions that motivated you to create a new platform?

There are a large number of other systems available for building data catalogs and tracking metadata, both open source and proprietary. What are the features of DataHub that would lead someone to use it in place of the other options? Who is the target audience for DataHub?

How do the needs of those end users influence or constrain your approach to the design and interfaces provided by DataHub?

Can you describe how DataHub is architected?

How has it evolved since yo

On this episode, we chat with former Sony Music Nashville VP of Digital Strategy Ed Rivadavia. Ed is originally from São Paulo, Brazil, but he spent much of his early years in Europe and the United States, learning three languages, other than Portuguese, along the way. Most recently a VP of Digital Strategy at Sony Music Nashville, where he worked with some of the biggest names in Country, Ed has always been — and still is — a metalhead at heart. What’s particularly interesting about Ed’s career is how you can trace the trajectory of the role of marketing in the music industry from radio promotion or “old media” marketing in the ‘90s, to trying to get a handle on ways to use the internet, or “new media,” in the early 2000s, and then to settling in to what we now know as digital marketing and digital strategy in the 2010s. Ed’s global and multi-genre experience imbues his perspective on digital trends in the music industry with nuance and prescience. Connect With Edhttps://www.linkedin.com/in/edrivadavia/ Connect With Ushttp://podcast.chartmetric.com/http://chartmetric.com/https://blog.chartmetric.comhttps://smarturl.it/chartmetric_social

Summary Event based data is a rich source of information for analytics, unless none of the event structures are consistent. The team at Iteratively are building a platform to manage the end to end flow of collaboration around what events are needed, how to structure the attributes, and how they are captured. In this episode founders Patrick Thompson and Ondrej Hrebicek discuss the problems that they have experienced as a result of inconsistent event schemas, how the Iteratively platform integrates the definition, development, and delivery of event data, and the benefits of elevating the visibility of event data for improving the effectiveness of the resulting analytics. If you are struggling with inconsistent implementations of event data collection, lack of clarity on what attributes are needed, and how it is being used then this is definitely a conversation worth following.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it? I’m working with O’Reilly on a project to collect the 97 things that every data engineer should know, and I need your help. Go to dataengineeringpodcast.com/97things to add your voice and share your hard-earned expertise. When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $60 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! If you’ve been exploring scalable, cost-effective and secure ways to collect and route data across your organization, RudderStack is the only solution that helps you turn your own warehouse into a state of the art customer data platform. Their mission is to empower data engineers to fully own their customer data infrastructure and easily push value to other parts of the organization, like marketing and product management. With their open-source foundation, fixed pricing, and unlimited volume, they are enterprise ready, but accessible to everyone. Go to dataengineeringpodcast.com/rudder to request a demo and get one free month of access to the hosted platform along with a free t-shirt. You listen to this show to learn and stay up to date with what’s happening in databases, streaming platforms, big data, and everything else you need to know about modern data platforms. For more opportunities to stay up to date, gain new skills, and learn from your peers there are a growing number of virtual events that you can attend from the comfort and safety of your home. Go to dataengineeringpodcast.com/conferences to check out the upcoming events being offered by our partners and get registered today! Your host is Tobias Macey and today I’m interviewing Patrick Thompson and Ondrej Hrebicek about Iteratively, a platform for enforcing consistent schemas for your event data

Interview

Introduction How did you get involved in the area of data management? Can you start by describing what you are building at Iteratively and your motivation for creating it? What are some of the ways that you have seen inconsistent message structures cause problems? What are some of the common anti-patterns that you have seen for managing the structure of event messages? What are the benefits that Iteratively provides for the different roles in an organization? Can you describe the workflow for a team using

Summary A majority of the scalable data processing platforms that we rely on are built as distributed systems. This brings with it a vast number of subtle ways that errors can creep in. Kyle Kingsbury created the Jepsen framework for testing the guarantees of distributed data processing systems and identifying when and why they break. In this episode he shares his approach to testing complex systems, the common challenges that are faced by engineers who build them, and why it is important to understand their limitations. This was a great look at some of the underlying principles that power your mission critical workloads.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management What are the pieces of advice that you wish you had received early in your career of data engineering? If you hand a book to a new data engineer, what wisdom would you add to it? I’m working with O’Reilly on a project to collect the 97 things that every data engineer should know, and I need your help. Go to dataengineeringpodcast.com/97things to add your voice and share your hard-earned expertise. When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $60 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! If you’ve been exploring scalable, cost-effective and secure ways to collect and route data across your organization, RudderStack is the only solution that helps you turn your own warehouse into a state of the art customer data platform. Their mission is to empower data engineers to fully own their customer data infrastructure and easily push value to other parts of the organization, like marketing and product management. With their open-source foundation, fixed pricing, and unlimited volume, they are enterprise ready, but accessible to everyone. Go to dataengineeringpodcast.com/rudder to request a demo and get one free month of access to the hosted platform along with a free t-shirt. You listen to this show to learn and stay up to date with what’s happening in databases, streaming platforms, big data, and everything else you need to know about modern data platforms. For more opportunities to stay up to date, gain new skills, and learn from your peers there are a growing number of virtual events that you can attend from the comfort and safety of your home. Go to dataengineeringpodcast.com/conferences to check out the upcoming events being offered by our partners and get registered today! Your host is Tobias Macey and today I’m interviewing Kyle Kingsbury about his work on the Jepsen testing framework and the failure modes of distributed systems

Interview

Introduction How did you get involved in the area of data management? Can you start by describing what the Jepsen project is?

What was your inspiration for starting the project?

What other methods are available for evaluating and stress testing distributed systems? What are some of the common misconceptions or misunderstanding of distributed systems guarantees and how they impact real world usage of things like databases? How do you approach the design of a test suite for a new distributed system?

What is your heuristic for determining the completeness of your test suite?

What are some of the common challenges of setting up a representative deployment for testing? Can you walk through the workflow of setting up, running, and evaluating the output of a Jepsen test? Ho

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts. This week on Making Data Simple, we have Ross Mauri General Manager, IBM Z & LinuxONE IBM Systems. Ross has expertise in strategy, technology, engineering, marketing, and sales. This week we discuss his career at IBM, the people and CEOs of IBM, Mainframes, Databases, Cloud, and Datastores, the myth of Z, and IBM's Z15.

Show Notes 3:43 - Ross Mauri's career 8:22 – People of IBM and CEOs 12:11 – Working with CEOs 14:34 – Ross talks legacy  17:20 – What does the mainframe do that no one else can? 18:28 – Z myth 21:22 – LinuxONE 24:29 – RedHat 25:15 – What does Z not do well? 26:00 – Z15 Ross Mauri - LinkedIn Connect with the Team Producer Kate Brown - LinkedIn. Producer Meighann Helene - LinkedIn. Producer Michael Sestak - LinkedIn. Producer Steve Templeton - LinkedIn. Host Al Martin - LinkedIn and Twitter.    Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

This audio blog discusses the Data Lakehouse, a marketing concept that evokes clean PowerPoint imagery, and why and how the New Cloud Data Lake will play a very real role in modern enterprise environments.

Originally published at: https://www.eckerson.com/articles/data-lakehouses-hold-water-thanks-to-the-cloud-data-lake

It sometimes seems like there must be a Moore's Law of marketing technology (or "martech," as the cool kids call it, and our site is on a .io domain, so we're definitely the cool kids) whereby the number of platforms available doubles every 6 to 8 weeks. And, every couple of months, it seems, a whole new category emerges. From CMS to DAM to CRM to TMS to DMP to DSP to CDP, it's an alphabet soup of TLAs that no one can make sense of PDQ! On this episode, Michael, Moe, and Tim sat down with the man who coined the name for one of those categories back in 2013: David Raab, the founder of the CDP Institute! It was a lively chat about the messy world of vendor overload and how to frame, assess, and successfully manage martech stacks. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Free Data Storytelling Training Attend our FREE 'How to be the Chief Data Storyteller in your Org - Part 2 using our Analytics Design Guide' training at webinars.bidatastorytelling.com and download the FREE 50-page Guide! In this episode, you'll learn: [02:30] Extra Step: Why quality assurance (QA) and substantive storytelling matters. [03:16] Key Quote: Data scientists are brilliant, but I see a lot of struggle with how to communicate that brilliance.-Mico Yuk [07:50] Kristen and Company: Working together to communicate and transform ML marketing and storytelling.
For full show notes, and the links mentioned visit: https://bibrainz.com/podcast/51

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Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.  Abstract This week on the podcast, our guest is Priya Doty, VP of Product Marketing at IBM. Priya specializes with the IBM Z and LinuxONE brands and shares her expertise in this episode.  Connect with Priya LinkedIn Twitter Medium IBM Blogs Show Notes 02:51 - Learn more on using SQL for Data Analysis here. 05:53 - Discover what B2B means here. 16:03 - You can find out more on pervasive encryption technology here. Connect with the Team Producer Liam Seston - LinkedIn. Producer Lana Cosic - LinkedIn. Producer Meighann Helene - LinkedIn.  Producer Mark Simmonds - LinkedIn.  Host Al Martin - LinkedIn and Twitter. Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

For our special International Women's Day episode, we committed a type one error and peeked at our results, so we are releasing this winner three days early. As good analysts, we set out to optimise the podcast by swapping out Tim and Michael for two guests (it's rare for Tim to be in the control group, but he's an outlier either way). Unfortunately, it turns out we confused testing with personalisation, so we invited along a family member, Michele Kiss, as well as CRO expert Valerie Kroll, to talk about the evolution of the space from conversion rate optimisation (CRO) to experimentation. In Val's words, good experimentation programs are all about optimising to de-risk product feature roll-outs and marketing tactics, all the while learning about our users and prospects. Stay tuned for the three tips from our guests on how to set up the best version of an experimentation framework, as well as the stats on the show's gender breakdown since our start in 2015! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.  Abstract This week on Making Data Simple, our guest is Aarti Cherian, Program Director for IBM's Cloud Pak for Data and Watson Data Science Marketing. Aarti discusses key marketing tactics that are currently leveraged by teams at IBM.  Connect with Aarti LinkedIn Twitter Show Notes 3:01 - Check out this article on marketing techniques for tech companies.  14:41 - Not sure what B to B means? Find out here. 21:24 - Learn more about IBM Cloud Pak for Data here. 21:28 - Learn more about IBM Cloud Pak for Data System here. Connect with the Team Producer Liam Seston - LinkedIn. Producer Lana Cosic - LinkedIn. Producer Meighann Helene - LinkedIn.  Producer Mark Simmonds - LinkedIn.  Host Al Martin - LinkedIn and Twitter. Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

Events, clickstream data or hits (as they are known in the world of Google Analytics) are the building blocks of all marketing analytics suites. In the past they have been processed and aggregated into prefabricated reports before we interact with them. With compute and storage costs dropping, using these raw hits suddenly becomes a viable and powerful option. They require some extra leg work to use but in return offer some great advantages including the ability to reprocess the data as many times as you see fit.

For most of us analytics have always been a tool for marketing. But if we drop the assumptions and look at the data we have as a source of insights for the whole organisation to explore how we can make new friends and what difference we can make for the organisation and business in general and not just the website and the online team.

How do you measure the impact of creativity? This is one of the major issues facing analytics in LEGO, since the majority of products are not being sold directly to consumers. Today, LEGO’s internal creative agency is providing thousands of creative communication and marketing assets to hubs all around the world in hundreds of different cultures, but the question remains how can you measure creative work’s productivity and efficiency and how do you determine the return on a creative marketing asset in a complex world?