Webinar Review: Oracle Big Data Cloud, Understanding Business

People at technology startups love to call the industry giants dinosaurs. The analogy fails for a number of reasons. The funniest is that the dinosaurs existed for many millions of years. As the large companies exist now, are the startups are saying the big companies will only disappear if we’re hit by a meteor? Companies became large by filling a need. While many might not be as nimble, their experience, especially in enterprise software, means they often see the needs of the business community while the small companies are focused too much on their “cool” technology.

This week’s Oracle webinar, hosted by the DBTA, was a good example of that. The speakers were Rich Clayton, VP Business Analytics Product Group, and Omri Traub, VP Software Development, and the subject was, no surprise, Oracle Big Data Cloud Service (OBDC. Yeah, I know. Too close to ODBC…). Before we get into the details, people need to be aware that Oracle is fully committed to the cloud, as pointed out in a recent advertorial in Forbes. Oracle is clearly competing with Amazon for enterprise cloud business. Big data is only one part of that.

Rich Clayton began the presentation by pointing towards Thomas Edison’s laboratory as an example of using the ideas from many people to not only invent things but also to figure out how to market those inventions. He brought that directly into the evolution of corporate data labs. The biggest problem, Rich stated, is that that labs are usually only populated by very technical people while they require a broader array of talents. That requirement is one of the data labs principles he defined and one I’ve also described as the missing component of many corporate data labs.DBTA Webinar - Oracle - Principles of the Data Lab

A related problem is that most products are so complex and silo’d that very technical people are needed. At this stage in business intelligence and big data, that’s the horse that needs to be addressed before the broad access cart can move.

Omri Traub then took over for the demonstration portion of the presentation. Unfortunately, he unintentionally proved the point about technical folks missing business needs by the setup he used for the demonstration. The demo was built around an enormous amount of information on New York City taxi information. While manipulating a billion record data set is cool and powerful, he never presented a business message. He pointed to the large volume of data, talked about other data sources he combined, and then played with the data to show correlations.

The problem? Omri, claimed we were gaining insight. Correlations aren’t insight. Understanding how those correlations might impact your business and ideas how to adapt business to meet what you find is insight. Nothing in the demonstration pointed towards insight.

Fortunately, Rich Clayton earlier had given a couple of case studies showing business insight gained by OBDC early customers. It would have been much better if Mr. Traub had focused on one of those cases or something similar.

The best point of the demonstration was when Omri showed how, in the middle of playing with some relationships, he easily incorporated some analysis created by a different person. As mentioned above, collaboration is critical and it looks like Oracle hasn’t limited that to just a marketing message but has worked to make sure that Oracle’s product helps the team. As many companies claim to do that and it was only an overview, your mileage might vary. Make sure when you talk to them to follow through and see whether the collaboration (not to mention the entire product…) meets your needs.

The final section was the Q&A. I’m a marketing person, so I have to be honest and state that it sounded like canned questions they wanted to address, as there was way too much about the full Oracle ecosystem brought into discussion at this point compared to what I’d expect from customers. Still, there was one important point.

A question was asked about what advanced analytics might be added. Mr. Taub had the perfect response. After quickly mentioning that, yes, Oracle was always looking at advanced analytics and how to add them, he made a much more important point. Collobaration is key and OBDC is designed to get business people involved. All analytics need to be added in a usable manner, in a way that is understandable and can be leveraged by more people than just the technical resources.

That is the critical viewpoint that a large, enterprise focused company can bring to BI, the cloud and big data. That’s why it’s foolish to write off the large companies, the ones with expertise in not just technology, but in business and business relationships. They might not move as fast, but they can move to the right places with the right products and the right business messages.

DBTA Webinar Review: Leveraging Big Data with Hadoop, NoSQL and RDBMS

A presentation last week, hosted by Database Trends and Applications (DBTA), was a great example of some interesting technical information presented poorly. As that sentence implies, this column is one about the marketing of business intelligence (BI), not about the technology – well, not much…

There were three presenters: Brian Bulkowski, CTO and Co-founder, Aerospike; Kevin Petrie, Senior Director and Technology Evangelist, Attunity; Reiner Kappenberger, Global Product Management, HPE Security – Data Security.

Aerospike

Brian was first at the podium. Aerospike is a company providing what they claim is a very high speed, scalable database, proudly advertising “NoSQL!” The problem they have is that they are one of many companies still confused about the difference between databases and SQL. A database is not the access method. What they’re really focused on in loosely structured data, the same way Hadoop and other newer databases are aimed. That doesn’t obviate the need to communicate via SQL.

He also said that the operational in-memory market is “owned by NoSQL.” However, there were no numbers. Standard RDBMS’s, columnar and NoSQL databases all are providing in-memory storage and processing. In fact, Information Management has a slide show of Gartner’s database analytics vendor report and you can see the breadth there. In addition, what I constantly hear (not statistically significant either…) is that Hadoop and other loosely-structured databases are still primarily for batch. However, as the slide show I just mentioned is in alphabetical order, and Aerospike is the first one you’ll see. Note again that I’m pointing out flaws in the marketing message, not the products. They could have a great in-memory solution, but that’s doesn’t mean NoSQL is the only NoSQL option.

The final key marketing issue is that he kept misusing “transactional.” He continued to talk about RDMS’s as transactional systems even while he talked about the power of Aerospike for better handling the transactions. In the later portion of his presentation, he was trying to say that RDBMS’s still had a place, but he was using the wrong term.

Attunity

Attunity’s Kevin Petrie was second and his focus was on Attunity Replicate. The team of Aerospike and Attunity again shows the market isn’t yet mature enough to have ETL and databases come smoothly together. Kevin talked about their 35 sources and it seem that they are the front end in the marketing paring of the two companies. If you really need heterogeneous data sources and large database manipulation, you’ll need to look at the pair of companies.

My key issue with this section was one of enterprise priorities. Perhaps the one big, anonymous reference they both discussed drove the webinar, but it shouldn’t have owned the message. Mr. Petrie spent almost all his time talking about Hadoop, MongoDB and Kafka. Those are still bleeding edge tools while enterprise adoption requires a focus on integrating with standard and existing sources. Only at the end, his third anonymous case, did Kevin have a slide that mentioned RDBMS sources. If he wants to keep talking with people running experimental and leading edge tests of systems, that priority makes sense. If he wishes to talk to the larger enterprise market, he needs to turn things around.

The other issue was a slide that equated RDBMS, Data Warehouse and Hadoop as being on equal footing. There he shows a lack of business knowledge. The EDW, as an old TV would declare, is the one of these things that is not like the other. It has a very different purpose from the two database technologies and isn’t technology dependent.

HPE Security

Reiner Kappenberger gave a great presentation but it didn’t belong. It seems the smaller two firms were happy to get HP to help with the financing but they didn’t think about staying on message.

Let me make it very clear: Security is of critical importance. What Mr. Kappenberger had to say was very important for people to hear. However, it didn’t belong in this webinar. The topic didn’t fit and working to stuff three presenters into forty minutes is always tough. Another presentation where all three talked about how they work to ensure that the large volumes of data can be secure at multiple levels would have been great to hear – and I hope the three choose to create such a webinar.

Summary

This was two different webinars stuffed into one, blurring the message. In addition, Aerospike and Affinity either need to make sure they they’re not yet trying to address the mass market or they need to learn how to stop speaking to each other and other leading edge people and begin to better address the wider enterprise market.

The unnamed reference seemed to be a company that needed help with credit card transactions and fraud detection, and all three companies worked to provide a full solution. However, from a marketing standpoint I don’t think they did proper service to their project by this webinar.

TDWI & Teradata: An overview of data-centric security

Yesterday’s TDWI webinar was focused on data-centric security. The tag team was Fern Halper, Research Director for Advanced Analytics, TDWI, and Jay Irwin, Director of InfoSec, Teradata. It’s always nice when the two halves of a sponsored presentation fit well. For that reason and for the content, this was a nice presentation.

Everyone in the industry knows that data breeches happen, and we all talk about the issue. I’ve seen a few articles and lists about the number of successful attacks, but Fern Halper pointed us to a nice graphic from Information is Beautiful. She also pointed to another study that showed that “In 2013, 33% of respondents said their company had a data breach. In 2014 the percentage has increased to 43%.” It’s always a race between black hats and white hats, so it’s important to minimize not only your chance of getting hacked, but also to minimize the importance and usefulness of data gained from successful hacks.

Ms. Halper than discussed four types of data security:

  • Perimeter security: monitoring network access for intrusion detection.
  • Authorization and Access: Password and role based data protections.
  • Encryption: Using cryptography to encode data.
  • Logging and monitoring: Analyzing access patterns.

Each part is necessary but insufficient. Authorization is only as strong as people’s passwords. If it’s easy to steal the encryption key, encryption doesn’t matter. A robust security system leverages all the types.

One important note: Later in her presentation and throughout Jay Irwin’s section, encryption didn’t exist alone but alongside tokenization. The later is a different security technology, where characters, words, numbers and fields are replaced with other symbols, or tokens, that still look as if they’re real and can still be used in analysis. Mr. Irwin pointed out he prefers “data protection” as a rubric that covers all the techniques of data level security.

Along with that clarification, Jay Irwin also described the multiple layers as “Defense in Depth,” a concentric ring of security to ensure there’s no single point of failure. Jay also provided my favorite slide of the presentation. While it’s too wordy, it’s a pretty clear view of Teradata’s top-down approach.Teradata data security top-down pyramid

An organization must start with understanding the rules and regulations that drive data security. Only then can you identify the data assets that need special attention in order to protect them from hackers.

Jay has a lot more to say in a lot more detail, and I won’t cover it all. While I blog about webinars so you don’t have to watch, this one’s an exception. If you want to get a good, broad view of core data security issues, take some time and listen to the webinar.

TDWI Webinar — Engaging the Business, again from the technologist’s perspective

This week’s TDWI hosted webinar was about engaging business and, once again, it came from the standpoint of technologists rather than from business. There were some very good things said. However, until our industry stops thinking of business knowledge workers as children to be tutored and begins to think about them as people whose knowledge is the core of what we must encapsulate, we’ll continue to miss the mark and adoption of solutions will remain slow.

The main presenter was David Loshin, President of Knowledge Integrity. He began the presentation with a slide that describes his view of the definition of “data driven,” including three main points:

  • Focus on turning data into actionable knowledge that can lead to increased corporate value.
  • Aware of variance that can cause inconsistent interpretation.
  • Coordination among data consumers to enforce standards for utilization.

We should all clearly understand that the first item is not new and was not created by the business intelligence (BI) industry. Business has always been data driven. What we’re able to do now is access far more data than ever before so that we can provide a more robust view of the corporation.

Inconsistent Data v Inconsistent Utilization

The second bullet is a core point. Mr. Loshin used a couple of example such as sales territory and other areas where definitions are fuzzy. One clear difference to me is one I directly experienced 25 years ago, and more directly addresses the visualization side of the BI conundrum. I was working for a major systems integrator (SI) and my client was, well, let’s just say it was a large, fruit based computing company.

A different SI had created an inventory system for the client’s manufacturing facility but the system was a failure though all the right data was in the system. The problem was that the reports were great for the accounting department, not for inventory and manufacturing. We interviewed the inventory team and then rewrote reports to address and present the information from their standpoint.

Too often, technologists get lost in the detailed data definitions and matching fields across data sources. That is critical, but it loses the big picture. Even when data is matched, different business people use data differently.

Which brings us to David Loshin’s third point. No, we don’t need to enforce exact standards for utilization. We need to ensure that the data each consumer refers to is consistent, but we must do a better job in understanding that different departments can utilize the exact same data in a variety of ways.

Business Drivers and Data Governance

David did get to the key issue a bit later, on a slide titled Operationalizing Business Policies. He points out that it’s critical to ensure that “Information policies model the data requirements for business policy.” This is key and should be bubbled up higher in the mindset of our industry. While I hear it mentioned often, it seems to be honored more in the breach.

Time was spent discussing the importance of understanding different users and their varying utilization of data. As I mentioned in the introduction, the solution to the new complexities then veers from addressing business needs to ignoring history. In a previous blog post, I discussed how many in the industry seem to be ignoring the lessons to be learned from the advent of the PC. Mr. Loshin seems to be doing that when he talks about empowering the business users to set their own usability rules. He splits IT and business in the following way:

  • Business data consumers are accountable for the rules asserting usability for their views of the data.
  • IT becomes responsible for managing the infrastructure that empowers the business user.

The issue I have with that argument is a phrase that didn’t appear in this webinar until Linda Briggs, the moderator, mentioned it in a poll question right before Q&A: Data Governance. Corporations are increasingly liable for how they control and manage information. It does not make sense to allow each user to define their own data needs in a void. Rather than allow for massively expanded and relatively uncontrolled access to data and then later have to contract access, as corporations had to regain a handle on what was being done on scattered desktop computers, BI vendors should be positioning data governance from the start.

Whether it’s by executive fiat, a cross-functional team, or some other method, companies need to clarify data governance rules. Often, IT is the best intermediary between groups, actively participating in data governance definition as an impartial observer and facilitator. It is then the job of IT to ensure that it provides as open access as possible to business workers given their needs and the necessity of following governance rules.

There was one question, during Q&A, on the importance of data governance. I thought David Loshin again understated its importance while Harald Smith, Director of Product Management at Trillium, the webinar sponsor, had the comment that “everyone is responsible for data governance.” That is my only mention of the sponsor, as I felt his portion of the presentation was a recitation of sound bites, talking points and buzz words that didn’t provide any value to the hour.

Summary

David Loshin has a clear view of engaging the business and gets a number of key things correct. However, that view is one of a technologist looking over a self-imagined bridge separating technology and business. There’s not a bridge separating IT and business. They overlap in many critical areas and both must learn from and work well with each other.

Yellowfin DashXML Webinar: Good new feature, not so good launch

The launch of Yellowfin DashXML included a round of global webinars mid-week. Well, not “included,” it’s more that the webinar was the entire launch. The new product feature is useful, but as I’m a marketing person I do have to question how they’ve handles the launch.

Yellowfin, as with many business intelligence (BI) vendors, is focused on visualization, providing business knowledge workers the ability to easily see information. The presentation was by John Ryan, Director of Product Marketing, and Teresa Pringle, Product Specialist. As is obvious from the title of the webinar, it was to announce the availability of the first version of DashXML, a utility within Yellowfin that allows easy integration of custom XML into dashboards and reports.

While they do sell directly to IT organizations who provide their interface to their corporate users, they also have a strong OEM business. As Mr. Ryan pointed out, “Embedding BI is a large chunk of Yellowfin’s business.” While direct label clients also want to customize user interfaces, DashXML seems much more valuable to the OEM customer base, providing an easier way to integrate standards from existing applications in order to have a more consistent interface.

The key word in that last sentence was “easier,” not “easy,” and that’s just fine for what is needed. This is XML. As Ms. Pringle explained, programmers will need to be very familiar with CSS manipulation and also with Java Script. DashXML is there to assist developers in providing customized visualizations, it is not for end users. The feature is available with a server license, providing deployment capability, and with a developer license for investigating the feature. It is not available as part of the per-user, distribution license for end users.

DashXML adds power and flexibility to Yellowfin’s offering and will better help its clients customize visualizations.

A Very Quiet Launch

As much as the presenters seemed to be working to imply DashXML is a new product, it’s really a feature of their platform. While the title of the webinar was a launch, nothing in the presentation or on their site implies it’s really a launch.

Almost the entire presentation was about the existing Yellowfin offering. Teresa Pringle’s “demo” portion of the webinar started with a whole lot of customized interfaces and only spent a few minutes showing the DashXML features in design and only for a single report in a dashboard. You could get the idea that it would make things easier, but it was also clear that’s all it did. There’s nothing really new, nothing that Yellowfin clients aren’t doing now, it’s a way to save time and money. Mind you, those are very valuable things, but the presentation didn’t focus on any ROI those savings might present.

What’s more intriguing is that they held a webinar, yet their site doesn’t reflect that knowledge. As of the writing of this blog entry (24 hours after the webinar), a few things seem to be missing:

  • No DashXML item in their home page rotating banner.
  • No DashXML mentioned on the rest of the home page.
  • No DashXML item on their news/blog page.
  • No DashXML added to their site menu, even though John presented a slide that implied DashXML was on the same level as their platform and web services offerings.

If the feature isn’t important enough to discuss on the web site, why have a webinar? After all, the purpose of a webinar is to drive interest in the product and one of the key follow ups for webinars should also be gaining information on your site to hopefully drive customer tracking and contact information as lead qualification.

DashXML is a nice addition that can help IT and OEM developers blend point-and-click development and coding to provide a customized visualization interfaces with better ROI. However, a week webinar and no content is neither a silent launch nor a strong one. Sadly, the marketing doesn’t rise to the quality of the product enhancement.