About TikTok and Privacy: $92 Million Catch Your Attention

March 4, 2021

I have commented about the superficial understanding shared among some “real” and big time journalists of data collection. What’s the big deal about TikTok? Who cares what kids are doing? Dismissive attitude flipped off these questions because “real” news knows what’s up?

ByteDance Agrees to US$92 Million Privacy Settlement with US TikTok Users” suggests that ignoring the China-linked TikTok may warrant some scrutiny. The story reports:

The lawsuits claimed the TikTok app “infiltrates its users’ devices and extracts a broad array of private data including biometric data and content that defendants use to track and profile TikTok users for the purpose of, among other things, ad targeting and profit.” The settlement was reached after “an expert-led inside look at TikTok’s source code” and extensive mediation efforts, according to the motion seeking approval of the settlement.

My view is that tracking a user via a range of methods can create a digital fingerprint of a TikTok user. That fingerprint can be matched or cross correlated with other data available to a specialist; for example, information obtained from Oracle. The result is that a user could be identified and tracked across time.

Yep, today’s young person is tomorrow’s thumbtyper in one of the outfits compromised by the SolarWinds’ misstep. What if the TikTok data make it possible to put pressure on a user? What if the user releases access information or other high value data?

TikTok, TikTok, the clock may be ticketing quietly away.

Stephen E Arnold, March 4, 2021

Is Business Intelligence the New Silver Bullet for Managers Who Want to Be Even More Intelligent?

February 15, 2021

Survey results from an outfit called Reveal contains some interesting market data. “Demand for Business Intelligence Solutions Increases by 41 Percent” provides some data about the sample size (120 developers and information technology Napoleons) but zero information about how these individuals were selected, the confidence level Reveal considers just peachy for the analysis, and other now old fashioned facets of a “survey” once taught in Statistics 101. Those YouTube videos about survey methods are good enough, thank you.

Here is one of the findings from the study:

A 41 percent increase in demand for business intelligence solutions in 2020.

Okay, financial, social, and political excitement, the Covid Rona thing, and the implosion of once boring business sectors like airlines, real estate, and local small businesses.

Business intelligence to the rescue with real time analyses of data, predictive analytics, and nifty charts and graphs.

Were there other findings from this remarkably amusing sample? Absolutely. To wit:

  • 50 percent had budgets chopped
  • 23 percent had projects killed
  • 14 percent lost staff and funding.

Popular buzzwords include the aforementioned predictive analytics, edge analytics which I assume means cloud based services like Amazon AWS, and “natural learning” which I possibly machine learning, AI, et al.

Net net: Let’s bet on business intelligence. Better, faster, and cheaper. Plus, managers will be able to make better decisions based on actionable intelligence. Sounds good, right?

Stephen E Arnold, February 15, 2021

Business Intelligence, Expectations, and Data Fog

February 10, 2021

Business intelligence and government intelligence software promises real time data intake, analysis and sense making, and outputs with a mouse click. Have you heard the phrase, “I have the Brooklyn Bridge for sale”? Sure, sure, I know I don’t want to own the Brooklyn Bridge, but that super spiffy intelligence software (what I call intelware), count me in.

The marketing pitch for business intelligence and general intelligence software has not changed significantly over the years. In my experience, a couple of nifty outputs like a relationship diagram and a series of buttons set up to spit out “actionable intelligence” often close the deal. The users of the software usually discover three points not making up a large part of the demos, the discussions, and the final contract for the customer’s requirements.

I read “The Age Of Continuous Business Intelligence.” The idea is appealing. Lots of information and no time to read, review, digest, analyze, and discuss the available information. In my opinion, the attitude now is “I don’t have time.”

Yep, time.

The write up asserts:

we [an outfit called KX] know that shortening the time it takes to ingest, store, process, and analyze historic and real-time data is a game changer for businesses in all sectors. Our customers in finance, manufacturing, automotive, telecommunications and utilities tell us that when processes and systems are continuously fed by real-time data that is enriched by the context of historic data, they can automate critical business decisions resulting in significant operational and commercial benefits.

The write up contains a diagram which lays bare “continuous business intelligence.”

image

The write up concludes:

As the research clearly shows, real-time data analytics is a critical area of investment for many firms. To ensure maximum value is derived from these investments, it is imperative that organizations – regardless of size and sector – challenge their understanding of what real-time means. By implementing a strategy of continuous business intelligence, firms can dramatically reduce the time it takes to uncover and act on insights that can materially change the game in terms of growth, efficiency and profitability.

I love that “research clearly shows.” The challenges for the continuous thing include:

  • Defining real time. (According to research my team did for a project years ago, there are numerous definitions of real time, and there is a Grand Canyon sized gap among these.)
  • Making clear the computational short cuts necessary to process “fire hoses”. (Yep, these compromises have a significant impact on costs, validity of system outputs, and the mechanisms for issuing meaningful outputs from sense making.)
  • Managing the costs. (Normalizing, verifying, processing, storing, and moving data require human and machine resources. Right, those things.)

Net net: Software whether for business or government applications in intelligence work only if the focus is narrow and the expectations of a wild and crazy MBA are kept within a reality corral. Otherwise, business intelligence will shoot blanks, not silver bullets.

Oh, KX is hooked up with a mid tier consulting firm. What’s that mean? A sudden fog has rolled in, and it is an expensive fog.

Stephen E Arnold, February 10, 2021

An Existential Question: What Do Business Intelligence Tools Do?

February 10, 2021

Business intelligence tools are integral for enterprise systems to achieve their optimum performance, but without technology expertise it is difficult to understand their importance. Towards Data Science explains how BI tools can help a business in the article, “What BI Tools Can Do—The Six Different BI Artifacts You Should Know.”

According to the article, the six BI artifacts are spreadsheets, OLAP cube, visuals (reports and dashboards), stories, graphs, and direct access. Most BI tools do not feature all six BI tools and neither do companies. This does not allow end users to work at their best. There are work arounds and smart end users know how to utilize them.

Each artifact has its weaknesses and the only way to solve them is work around them like when there is a lack of tools:

“We basically have to do the same thing we do in the rest of our software architecture. We can build modular things, architectures where we can quickly exchange the EL in our EL (T). Where we can quickly exchange our storage, our reporting tool for a notebook based architecture. We can build evolutionary architectures, where we are perfectly clear on our fitting function, the quality of our answers to current problems. Where we know we will take small iterative steps towards providing better answers.”

It helps to be versed in all tools to improve BI structure, but it is even better to have access to the entire toolbox. Developers and workers are only as good as their tools.

Whitney Grace, February 10, 2021

Dashboards Evil? Worth a Thought. Nah, Just Take What Is Output

February 1, 2021

Business intelligence (BI) is jargon for the technologies and strategies used to manage business data analytics. It is a fancy term for standard operating procedures and looks good on a resume, but one IT CEO wants to make it obsolete. Diginomica discusses how BI could head to the recycling bin in the article: “ThoughtSpot CEO-‘I Want To Kill BI And I Want All Dashboards To Die.’”

COVID-19 has changed global business practices and technology experts spent 2020 investigating ways to aggregate business data. ThoughtSpot CEO Sudheesh Nair explained in the article that traditional aggregation patterns do not apply anymore and companies need to change in order to maintain their customers. Nair believes his ThoughtSpot platform, described as ‘Google for numbers,’ will deliver key insights the same way Google provides information.

Nair pointed out that opinions are easily accessible via a Google search, but facts are harder to find in the endless search results. Nair wants his ThoughSpot platform to make facts as easily accessible as opinions. ThoughtSpot combines hardened facts with a NLP interface to make finding facts easier, think Windows 95 versus the old command land interface:

“ThoughtSpot does this by allowing users to search enterprise data with hyper-personalized questions using natural language processing. It aims to not only give a result for the question you ask, but then also uses AI to offer up alternative questions and results that may be helpful. This is very different to traditional BI, which typically offers you a template for which to present historical, aggregate data.”

In other words, Nair wants to sift the information noise from facts. Today’s BI dashboards offer a plethora of information, but lack personalization notes that could win new customers and retain older ones.

ThoughtSpot will supposedly combine old data with new data to push out BI dashboards and create a new data analytics space for businesses. Nair’s description of ThoughtSpot is an interesting pitch, but it sounds more like a new way to search information. Instead of explaining how ThoughtSpot works it would be better to offer demonstrations of its capabilities.

But thinking? Not the core competency of the thumb typing generations.

Whitney Grace, February 1, 2021

InterSystems Releases BI Tool Adaptive Analytics

November 5, 2020

Data technology firm InterSystems is launching an addition to its IRIS platform, IRIS Adaptive Analytics. ChannelLife reports, “InterSystems Releases Solution for Self-Service BI.” InterSystem’s platform already provided data integration, data management, and analytics tools to its clients in the fields of finance, healthcare, business, and government. Adaptive Analytics adds advanced data analytics designed for use without having to call in the IT department at every turn. We learn:

“The solution provides business users with ease of use and self-service analytics capabilities to visualize, analyze, and interrogate live data and get the information they need in order to make business decisions without being experts in data design while providing the ability for IT and data stewards to apply centralized control. … The new solution provides seamless integration between live data in InterSystems IRIS and popular third-party business intelligence (BI) tools including Tableau, as well as Microsoft Power BI and Microsoft Excel. InterSystems IRIS Advanced Analytics simplifies the process for data designers to manage a common analytic data model and for business users to create and modify BI dashboards without needing IT involvement. The Adaptive Analytics solution also extends the scalability of InterSystems IRIS to support analytic workloads with larger data sets. … InterSystems IRIS Adaptive Analytics adds relational online analytical processing (ROLAP) capabilities to complement the existing multidimensional online analytical processing (MOLAP) capabilities already offered with InterSystems IRIS.”

InterSystems partnered with data virtualization firm AtScale to develop Adaptive Analytics, and it announced the development at its recent InterSystems Virtual Summit 2020. The new solution will be available in an upcoming IRIS release. Based in Cambridge, Massachusetts, InterSystems was founded back in 1978.

Cynthia Murrell, November 5, 2020

Web Scraping Made Easier

October 14, 2020

If one has a list of Web sites of interest, how can a person suck down the content? In the consumerized world of business intelligence, the answer is, “Every day.” Crawling Web sites is getting easier. Scrape Owl wants to make the process ever simpler. For as little as $30 per month you can chug along with 250,000 API calls and 10 concurrent requests. If you need more scraping horsepower, sign up for the $100 per month service. You use Scrape Owl’s API and can custom headers, cookies, and inject JavaScript. The more expensive service also allows proxies. These can be helpful under certain circumstances because some site operators are not keen on slurping. For more information, navigate to Scrape Owl’s FAQ page and take your first steps to becoming the new Google.

Stephen E Arnold, October 14, 2020

2020: Reactive, Semi-Proactive, and Missing the Next Big Thing

July 27, 2020

I wanted to wrap up my July 28, 2020, DarkCyber this morning. Producing my one hour pre recorded lecture for the US National Cyber Crime Conference sucked up my time.

But I scanned two quite different write ups AFTER I read “Public Asked To Report Receipt of any Unsolicited Packages of Seeds.” Call me suspicious, but I noted this passage in the news release from the Virginia Department of Agriculture and Consumer Services:

The Virginia Department of Agriculture and Consumer Services (VDACS) has been notified that several Virginia residents have received unsolicited packages containing seeds that appear to have originated from China. The types of seeds in the packages are unknown at this time and may be invasive plant species. The packages were sent by mail and may have Chinese writing on them. Please do not plant these seeds.

And why, pray tell. What’s the big deal with seeds possibly from China, America’s favorite place to sell soy beans? Here’s the key passage:

Invasive species wreak havoc on the environment, displace or destroy native plants and insects and severely damage crops. Taking steps to prevent their introduction is the most effective method of reducing both the risk of invasive species infestations and the cost to control and mitigate those infestations.

Call me suspicious, but the US is struggling with the Rona or what I call WuFlu, is it not? Now seeds. My mind suggested from parts unknown that perhaps, just perhaps, the soy bean buyers are testing another bio-vector.

As the other 49 states realize that they too may want to put some “real” scientists to work examining the freebie seeds, I noted two other articles.

I am less concerned with the intricate arguments, the charts, and the factoids and more about how I view each write up in the context of serious thinking about some individuals’ ability to perceive risk.

The first write up is by a former Andreessen Horowitz partner. The title of the essay is “Regulating Technology.” The article explains that technology is now a big deal, particularly online technology. The starting point is 1994, which is about 20 years after the early RECON initiatives. The key point is that regulators have had plenty of time to come to grips with unregulated digital information flows. (I want to point out that those in Mr. Evans’ circle tossed accelerants into the cyberfires which were containable decades ago.) My point is that current analysis makes what is happening so logical, just a half century too late.

The second write up is about TikTok, the Chinese centric app banned in India and accursed of the phone home tricks popular among the Huawai and Xiaomi crowd. “TikTok, the Facebook competitor?’s” point seems to be that TikTok has bought its way into the American market. The same big tech companies that continue to befuddle analysts and regulators took TikTok’s cash and said, “Come on down.” The TikTok prize may be a stream of free flowing data particularized to tasty demographics. My point is that this is a real time, happening event. There’s nothing like a “certain blindness” to ensure a supercharged online service will smash through data collection barriers.

News flash. The online vulnerabilities (lack of regulation, thumb typing clueless users, and lack of meaningful regulatory action) are the old threat vector.

The new threat vector? Seeds. Bio-attacks. Bio-probes. Bio-ignorance. Big, fancy thoughts are great. Charts are wonderful. Reformed Facebookers’ observations are interesting. But the now problem is the bio thing.

Just missing what in front of their faces maybe? Rona masks and seed packets. Probes or attacks? The motto may be a certain foreign power’s willingness to learn the lessons of action oriented people like Generals Curtis LeMay or George Patton. Add some soy sauce and stir in a cup of Sun Tzu. Yummy. Cheap. Maybe brutally effective?

So pundits and predictive analytics experts, analyze but look for the muted glowing of threat vector beyond the screen of one’s mobile phone.

Stephen E Arnold, July 27, 2020

Another Dust Up: A Consequence of Swisherism?

July 3, 2020

I associate Silicon Valley journalism with the dynamic duo of Swisher and Mossberg. The Walt has retired from the field of battle—almost. Kara Swisher sallies forth. The analytic approach taken by the “I” journalist has had a significant impact on others who want to reveal the gears, levers, and machine oil keeping the Silicon Valley factories running the way their owners and bankers intended.

Hence, Swisherism which I define as:

A critical look at Silicon Valley as a metaphor for the foibles of individuals who perceive themselves as smarter than anyone else, including those not in the room.

A good example of Swisherism’s consequences appears in “Silicon Valley Elite Discuss Journalists Having Too Much Power in Private App.” The write up is like a techno anime fueled with Jolt Cola.

For example:

During a conversation held Wednesday night on the invite-only Clubhouse app—an audio social network popular with venture capitalists and celebrities—entrepreneur Balaji Srinivasan, several Andreessen Horowitz venture capitalists, and, for some reason, television personality Roland Martin spent at least an hour talking about how journalists have too much power to “cancel” people and wondering what they, the titans of Silicon Valley, could do about it.

This is inside baseball given a dramatic twist. Big names (for some I suppose). A country-club app for insiders. An us versus them plot line worthy of Homer. The specter of retribution.

Yikes.

Even more interesting is that the article references a “recording” of what may have been perceived as a private conversation.

There’s nothing to inspire confidence like leaked recordings, right?

There is a sprinkling of foul language. A journalist becomes the target of interest. There is loaded language like “has been harassed and impersonated” to make sure that the reader understands that badness of the situation.

Swisherisms? Sort of, but the spirit is there. The under dog needs some support. Pitch in. Let’s make attitudes “better.” Rah rah.

I particularly like the use of Twitter as a weapon of myth destruction:

Lorenz’s tweet was immediately tweeted about by several Silicon Valley venture capitalists, most notably Srinivasan, who eventually made a seven-tweet thread in which he suggested Lorenz, and journalists like her, are “sociopaths.” That same day, a self-described Taylor Lorenz “parody” Twitter account started retweeting Srinivasan and other tech investors and executives critical of her work. The account’s bio also links to a website, also self-described as parody, which is dedicated to harassing Lorenz. (Twitter told Motherboard it deleted another account for impersonating Lorenz.)

“Lorenz” is the journalist who became the windmill toward which the Silicon Valley elite turned their digital lances.

Net net: Darned exciting. New type of “real” journalism. That’s the Swisherism in bright regalia. Snarkiness, insults, crude talk, and the other oddments of Silicon Valley excitement. No one like constructive criticism it seems. Politics, invective, overt and latent hostility, and a “you should do better” leitmotif. Sturm und drang to follow? Absolutely.

Stephen E Arnold, July 3, 2020

Business Intelligence: When Case Studies Are Not

June 25, 2020

A case study in the good old days was a little soft, a little firm, and a lot mushy. The precise definition of a case study is “it depends.” The problem is that case studies are often not easily duplicated. The data collection methods vary because many organizations do not keep data or, if kept, do not maintain data in a consistent manner. There’s a bright young sprout who wants data in a format unintelligible to other people and maybe systems.

Other minor potholes wander through thickets of subjectivity and into the mysterious world of sparse data. Ever heard, “Well, we don’t have that data, but we can take the inverse of these data and use them.”

The silly idea of answer who, what, why, where, where, and how are often discarded because the information is not available, secret, or just too much work. Just because you know. Meetings.

I thought about the murky world of case studies when I read “5 Valuable Business Intelligence Use Cases for Organizations.” First, there is the word “valuable.” Second, there is the phrase “business intelligence.” Third, there is the jargon “use cases.” Examples is a useful word. Why not employ it?

What caught my attention was that the examples illustrate the type of effort a group of volunteers make when no one wants to work very hard. You may have participated in filling a food basket with canned goods which few would actually consume.

Let’s look at one “use case,” and I will leave it to you to dig through the other four.

Use case number 2 explains how business intelligence can speed up and make better decision making manifest themselves. Okay, we have this pandemic thing. We have a bit of a financial downturn. We have the disruption of supply chains. We have the work from home method. We have Zoom solutions to knit together humans who like to hang out in break rooms and share gossip.

The fix is to use business intelligence to bring

together data mining, data analysis and data visualization to give executives and other business users a comprehensive view of enterprise data, which they can then use to make business decisions in a more informed way.

Now what do these terms mean? Data mining, data analysis, and data visualization. Where to the data come from? Are the data valid? Are the data comprehensive?

The “evidence” in the example is a survey conducted in a sample of an unknown number. The sample which may or may not be representative reports that “reliable data” is a hurdle. No kidding.

The case explains that the shift to real time data is important. Plus real time data piped into predictive analytics allows “fast action.”

The conclusion: Instantaneous decisions are possible.

Net net: The write up is a fluffy promotion of a nebulous concept. Use case my foot! I made an instant decision. Business intelligence like knowledge management and content management is a confection.

That’s why crazy “use case” explanations are needed. The other four examples in the article? Similar. Disconnected. A food basket filled with stuff no one will consume.

Stephen E Arnold, June 25, 2020

Next Page »

  • Archives

  • Recent Posts

  • Meta