Data. Our industry really loves that word, making it seem like the whole world revolves around it. We certainly enjoy revolving a lot of words around it. We put words like master, big, and meta before it, and words like management, quality, and governance after it. This spins out disciplines
Tag: data management
For many industries, big data analytics have opened numerous doors for more employees to be groundbreaking and to challenge the corporate status quo. Prior to big data technologies, risk taking behaviors were primarily reserved for provocative souls who stretched organizational boundaries to disrupt industries, such as airline revenue management. There were winners and losers
With big data, data governance challenges escalate in many ways: The diversity of data sources means that there are minimal standards for data structure, definition, semantics and content. The lack of control over data production means that you can’t enforce data quality at the source as you can do with
Marketers are walking a tightrope today with data privacy issues: Data can simultaneously bring customers and brands together and further drive them apart. Recent data breaches, potential changes in data-privacy legislation and regulations loom large as customer expectations concerning marketing data continue to rise. As a result, today’s complex data
At a recent MESA - Hollywood IT Society Digital Marketing conference, Claudio Ludovisi, SVP, Operational Strategy NBCU Entertainment for Marketing & Digital took a live poll of about 200 or so media marketing executives in the audience and asked them to “Think about what it takes to achieve true multiplatform
The Global Hadoop market was valued at $1.5 billion in 2012 and is expected to grow at a compound annual growth rate of 58.2 percent, to reach $50.2 billion by 2020, according to a Hadoop Market Analysis report prepared by Allied Market Research. There is no doubt that IT teams are
How many times a day do you search (or “Google”) how to do something with a product, the best ways to perform “X,” or for help with a problem? Chances are it’s a lot, and when you do, you likely land on a forum where your peers have posted answers
.@philsimon on title inflation.
Since my opening blog post about our new partnership with British Rowing and the GB Rowing Team, I’ve had a deep dive into their data, and we’re now close to our first key milestone – having all the data about a rower in a single location, so we can then
At most banks, data is stored in separate databases and data warehouses. Customer data is stored in marketing databases, fraud analyses are done on transactional data, and risk data is stored in risk data warehouses. Oftentimes even liquidity, credit, market, and operational risk data is stored separately as well. Bringing
So, you've heard the Hadoop hype and you are looking – or have already invested – into Hadoop. Maybe you have also realized some benefits from the Hadoop ecosystem. But now you want to maximize those benefits by using advanced analytics, or you might have heard about algorithms or machine learning libraries available
Would you build a house without a proper foundation? Most of us wouldn’t dare, but that’s exactly what many retail businesses are doing today. When building a house, if you don’t get the foundation right, paint, wallpaper and fixtures won’t matter much. It’s no different in the retail industry. Success
People often talk about the customer experience and the engagement model. This is an easier task when a business has regular interactions with its customers like banks and retailers. However, for insurers, this is a challenge. First of all, insurers have infrequent interactions with their customers. When there is interaction,
.@philsimon on the importance of timing.
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Imagine this situation: You go to you doctor and tell her that "something hurts in the lower chest area." Now, based on this short description of your pain, you expect her to come up with a precise diagnosis and a specific therapy suggestion, including treatment time and associated cost. Sound
Capital investment in production capability is the weakest link in the business value chain. It always has been and likely always will be. It’s the driving force behind the tendency towards cartels, collusion and monopolies. While it can make the first entrant into a brand new market, in the long
Okay, let's say your data is in Hadoop. The distributed, open source framework is configured as it should be across low-cost servers and your data is sitting in those clusters. It's been a meaningful effort to get to this point but how does it benefit your organization? If it's not doing something
Writing my previous post about digital banks got me thinking about the widespread use of analytics. In his book Digital Bank, Chris Skinner states that data should be seen as the most critical asset for digital banks. Actually, this holds true for almost every company nowadays. If you don’t have data of
Perhaps you're a big data expert who is fluent in Pig, Hive, MapR and all the technologies associated with the open source big data framework. Or maybe your role hasn't yet been touched by the increasingly popular Hadoop system. It's certainly worth a few minutes of your time (or perhaps
While managing quality within the four walls of your own operation is all well and good and totally necessary, both the market and your bottom line are demanding a more holistic, quality lifecycle approach, and in support of that aim there is a treasure trove of downstream data waiting to be
Principle 13: Remedial actions and supervisory measures - Supervisors should have and use the appropriate tools and resources to require effective and timely remedial action by a bank to address deficiencies in its risk data aggregation capabilities and risk reporting practices. Supervisors should have the ability to use a range
Having spent a good part of my career “owning” the data hub in IT for analytics solutions, I think I can say, the myth that IT controls all things data has become less and less true through the years – and eventually it will be completely false. Or maybe it
Principle 11: Risk management reports should be distributed to the relevant parties while ensuring confidentiality is maintained. Early in 2013, the Basel Committee on Banking Supervision (BCBS) issued guidelines for banks regarding risk data aggregation and reporting. Known collectively as BCBC 239, these principles were designed to ensure that banks
From managing excess DVD inventory to optimizing digital distribution channels, Hollywood’s supply chain transformation in the last decade has been massive. Knowing this background, and having spent a good part of my life surrounded by the entertainment industry, I was intrigued and inspired by the recent Entertainment Supply Chain Academy
How Internal Communications got into the video business. Everybody loves video. Well, maybe not everybody, but judging by the popularity of YouTube and the ubiquity of Web videos in general, I’d have to conclude that a mighty large chunk of the population loves – or at least likes – it.
Oil companies are being forced to explore in geologically complex and remote areas to exploit more unconventional hydrocarbon deposits. New engineering technology has pushed the envelope of previous upstream experience. No guidebook existed on how computing methodologies can contribute to E&P performance at reduced risk. Until now. A new book
Principle 9: Risk management reports should communicate information in a clear and concise manner. Reports should be easy to understand yet comprehensive enough to facilitate informed decision-making. Reports should include meaningful information tailored to the needs of the recipients. While the data management and data aggregation principles have been heavily
Principle 7: Accuracy - Risk management reports should accurately and precisely convey aggregated risk data and reflect risk in an exact manner. Reports should be reconciled and validated. Successful demonstration of Principle 7 requires senior management to rely upon the information presented in risk reporting. Since forward-looking strategic decisions are
Data federation is a relatively new term used to describe a form of data virtualization. Data virtualization, however, is not new. It has been around since at least the 1960's when virtual memory was introduced to simulate additional memory beyond what was physically available on a machine. While data federation is a