Google: Business Intelligence, Its Next Ad Business
October 11, 2022
Google has been a busy beaver. One example popped out of a ho hum write up about Google management’s approach to freebies. The write up “Google’s CEO Faced Intense Pushback from Employees at a Town Hall. His 2-Sentence Response was Smart Leadership” contains a rather startling point, if the article is accurate. Here’s the passage which is presumably a direct quote from Sundar Pichai, the top Googler:
Look, I hope all of you are reading the news, externally. The fact that you know, we are being a bit more responsible through one of the toughest macroeconomic conditions underway in the past decade, I think it’s important that as a company, we pull together to get through moments like this.
Did you see the crazy admission: “being a bit more responsible”. Doesn’t this mean that the company has been irresponsible prior to this announcement. I find that amusing: More responsible. Does responsibility extend beyond Foosball and into transparency about alleged online ad fraud or the handling of personnel matters such as the Dr. Timnit Gebru example?
But to the business at hand: Business intelligence. Like enterprise search and artificial intelligence, I am not exactly sure what business intelligence means. To the people who use spreadsheets like Microsoft Excel, rows and columns of data are “business intelligence.” But there must be more than redos of Lotus 1-2-3?
Yes, there are different ways to “do” business intelligence. These range from listening in a coffee shop to buying data from a third party provider and stuffing the information into Maltego to spot previously unnoticed relationships. And there are, of course, companies eager to deliver search based applications to make finding a competitor’s proposal to a government agency easier than figuring out which Google Dork to use.
“Google Days It’s Cracked the Code to Business Intelligence” explains that the Google is going to make BI as business intelligence is known to those in the know the King of the Mountain. I noted this passage:
In business intelligence [BI], “there was always this idea of governing BI and of self-service, and there was no reconciliation of the degree of trust and the degree of flexibility,” Google’s Gerrit Kazmaier told reporters last week, ahead of the Google Cloud Next conference. “At Google, I think we have cracked that code to how you get trust and confidence of data with the flexibility and agility of self-service.”
This buzzword infused statement raises several fascinating ideas. Let’s look at a couple of them, shall we?
First, the idea of “governance.” That’s a term to which I can say I don’t know what the heck it means. But the notion of “governance” and “trust” is that somehow the two glittering generalities are what Google has “cracked.” I must say, “What’s the meaning, Gerrit Kazmaier?”
Second, I noted three buzzwords strung together like faux silver skulls on a raver’s necklace: Trust, confidence, flexibility, and agility. To me, these words mean that more users want a point-and-click solution to answer a question about a competitor or the downstream impacts of an event like sanctions on China. The reality is that like the first buzzword, these don’t communicate, they evoke. The intention is that Mother Google will deliver business intelligence.
The solution, however, is not one Google crafted. The company’s professionals could not develop a business intelligence solution. Google had to buy one. Thus, the code cracking was purchased in the form of a company called Looker. The appeal of the Looker solution is that the user does not have to figure out data sources, determine if the data are valid, wrestle to get the data normalized, run tests to determine if the data set meets the requirements of a first year statistics class problem, and figure out what one needs to know. Google will make these steps invisible and reduce knowledge work to clicking an icon. There you go. To be fair, other companies have similar goals. These range from well known US companies to small firms in Armenia. Everyone wants to generate money from easy business intelligence.
Google is an online advertising business. The company wants to knock Microsoft off its perch as the default vendor to business and government. The Department of Defense is going to embrace the Google Cloud. I am not sure that some DoD analysts will release their grip on Microsoft PowerPoint, however.
Can a company trust Google? Does Google have a mechanism for governance for data handling, managing its professional staff (hello, Dr. Gebru), and ensuring that automated advertising systems are straight and true? Does Google abandon projects without thinking too much about consequences (hello, Stadia developers and customers)?
My hunch is that reducing business intelligence from a craft to a mouse click sets the stage for:
- Potential embedded and intentional data bias
- Rapid ill-informed decisions by users
- A way to inject advertising into a service application and personalization.
Will the days of the free car washes return to the Google parking lot? Will having meetings in a tree house in the London office become a thing again? Will Google displace other vendors delivering search based applications which engage the user in performing thoughtful analyses?
Time will provide the answer or rather Looker will provide the answer. Google will collect the money.
Stephen E Arnold, October 11, 2022
Salesforce, Alibaba, and China: Is an Enterprise Superapp the Goal?
August 4, 2022
I read an announcement about a tie up among Salesforce, Alibaba, and whoever is over-seeing the high profile online outfit. “Salesforce Shutters Hong Kong Office, Leans on Alibaba in China” reports:
As a result of its tightened partnership with Alibaba, Salesforce is “optimizing our business structure to better serve the Greater China Region” and “opening new roles while eliminating some others,” the spokesperson said. The company’s career page shows it’s currently hiring a product management director and a senior software engineer in the southern Chinese city Guangzhou, where it placed its tech team.
The cited article points out:
Salesforce’s interest in China lies in serving international businesses localizing in China, but it can’t do it alone due to the country’s intricate regulatory restrictions.
What will Alibaba do?
Alibaba will be taking over the firm’s sales in mainland China and Hong Kong, while Taiwan will fall under the management of its Singapore office…
Several observations:
- Like Oracle, Salesforce is taking steps to make sure it is able to operate in some acceptable way in China
- The technology for these deals is probably sealed in a quantum secure container so that “partners” are unable to learn what’s in the black boxes. (Well, that’s the hope?)
- China faces some challenges, and it is possible that Alibaba’s overseers could make helpful suggestions which make this tie up less or completely unattractive.
What happens if Alibaba integrates Salesforce functionality into its apps and services? Will we have a commercial superapp purpose built for China and companies permitted to operate in the Middle Kingdom?
Net net: Nah, just “lean on” and lean in.
Stephen E Arnold, August 4, 2022
Swedish Radio Tunes In to the Zuckbook Baloney
June 30, 2022
Sveriges Radio AB or Swedish Radio is a combo of the US National Public Radio and a “real” newspaper. In general, this approach to information is not the core competency of the Meat (sorry, Meta) Zuckbook thing. An interesting case example of the difference between Sveriges Radio and the estimable Silicon Valley super company is described in “Swedish Radio Created Fake Pharmacy – Reveals How Facebook Stored Sensitive Information.”
The main idea is that the Sveriges team did not listen to much disco or rap. Instead the canny outfit set up a honey pot in the form of a fake pharmacy. Then Sveriges analyzed what Facebook said it did with health-related information versus what the the Zuckster actually did.
Guess how that turned out? The write up explains:
After four days, 25 000 fake visits from customers had been registered with Facebook. But they had neither shut down nor warned the owners of the made-up pharmacy – Swedish Radio News’ reporters. When the reporters log into their account, they see that Facebook has stored the type of sensitive information that they say their filter is built to delete again and again. The question that the reporters then asked themselves was whether or not Facebook even has a filter that works in the Swedish language. One of the pharmacies that Swedish Radio reported on say that they cannot find any warnings from Facebook on data transfers that have taken place. The other has not wanted to answer the question. According to state investigators in the USA last year, Facebook only filtered in English.
Interesting? Yes, for three reasons:
- The radio outfit appears to have caught the Zuckers in a bit of a logical problem: Yes, there are filters? No, we just do marketing speak.
- Dismissing the method used to snap a mouse trap on Zuck’s big toe is probably a mistake. The “I’ll get back to you, Senator” works in the lobby-rich US. In Sweden, probably the method will swim like a plate of Surströmming.
- “Real” news — at least in Sweden — still has value. Perhaps some of the US “real” news people will give the approach a spin without the social justice and political sheen.
Net net: Will Facebook change its deep swimming in the information ocean? Has the Atlantic herring changed in the last two decades?
Stephen E Arnold, June 30, 2022
Apple: Intense Surveillance? The Core of the Ad Business
June 28, 2022
I read “US Senators Urge FTC to Investigate Apple for Transforming Online Advertising into an Intense System of Surveillance.” The write up reports:
Apple and Google “knowingly facilitated harmful practices by building advertising-specific tracking IDs into their mobile operating systems,” said the letter, which was signed by U.S. Senators Ron Wyden (D-Oregon), Elizabeth Warren (D-Massachusetts), and Cory Booker (D-New Jersey), as well as U.S. Representative Sara Jacobs (D-California).
There are references to Tracking IDs, “confusing phone settings, and monitoring a user when that user visits non-Apple sites and services. Mais oui! Surveillance yields data. Data allows ad targeting. Selling targeted ads generates money. Isn’t that what the game is about? Trillion dollar companies have to generate revenue to do good deeds, make TV shows, and make hundreds of thousands of devices obsolete with a single demo. Well, that’s my view.
Will something cause Apple to change?
Sure. TikTok maybe?
Stephen E Arnold, June 27, 21022
AlphaSense Downloads Some Bucks
May 3, 2022
AlphaSense is a market intelligence platform utilized by businesses to extract insights from 10,000 business sources, including SEC filings, news sources, analyst research, and transcripts. AlphaSense prides itself on assisting companies to save time and discover important market information that is translated into profits. Alley Watch details the business platform’s latest round of fundraising: “AlphaSense Raises $180M For Its Market Intelligence And Search Platform For Businesses To Be In The Know.”
The article is an interview with AlphaSense’s CEO Jack Kokko, who stated that the investors in the Series C fundraising were Goldman Sachs Asset Management, Morgan Stanley, AllianceBernstein, Viking Global Investors, City, Cowen Inc., Barclays, Wells Fargo Strategic Capital, Bank of America, as well as their past investors. He also highlighted the services AlphaSense offers and what makes it different from its competition:
“AlphaSense is a market intelligence and search platform for businesses. It leverages AI and natural language processing technology to extract relevant insights from an extensive universe of public and private content, including over 10,000 premium business sources. Without AlphaSense, people would lack a reliable way to find the mission-critical information that matters, given how disparate and inaccessible much of it is. We enable professionals to make critical decisions with confidence and speed, improving their business performance and outcomes.”
What appears to make AlphsaSense different is its AI-enabled tech teamed with NLP that locates pertinent information and then delivers it in a user-friendly manner.
Kokko started AlphaSense because when he worked at Morgan Stanley he found the current search technology lacking. He partnered with Rag Neervannan to launch AlphaSense in 2011 to create a platform that would fill a niche. Kokko was proud that during this round of investing many of his clients invested in AlphaSense. With the funding, he plans to invest in product development, expand in new territories and languages, and hire more employees.
Whitney Grace, May 3, 2022
DarkCyber for January 18, 2022 Now Available : An Interview with Dr. Donna M. Ingram
January 18, 2022
The fourth series of DarkCyber videos kicks off with an interview. You can view the program on YouTube at this link. Dr. Donna M. Ingram is the author of a new book titled “Help Me Learn Statistics.” The book is available on the Apple ebook store and features interactive solutions to the problems used to reinforce important concepts explained in the text. In the interview, Dr. Ingram talks about sampling, synthetic data, and a method to reduce the errors which can creep into certain analyses. Dr. Ingram’s clients include financial institutions, manufacturing companies, legal subrogration customers, and specialized software companies.
Kenny Toth, January 18, 2022
Business Intelligence: Popping Up a Level Pushes Search into the Background
January 17, 2022
I spotted a diagram in this Data Science Central article “Business Intelligence Analytics in One Picture.” The diagram takes business intelligence and describes it as an “umbrella term.” From my point of view, this popping up a conceptual label creates confusion. First, can anyone define “intelligence” as the word is used in computer sectors. Now how about “artificial intelligence,” “government intelligence,” or “business intelligence.” Each of these phrases is designed to sidestep the problem of explaining what functions are necessary to produce useful or higher value information.
Let’s take an example. Business intelligence suggests that information about a market, a competitor, a potential new hire, or a technology can be produced, obtained (fair means or foul means), or predicted (fancy math, synthetic data, etc.) The core idea is gaining an advantage. That is too crude for many professionals who are providers of business intelligence; for example, the mid tier consulting firms cranking out variations of General Eisenhower’s four square graph or a hyperbole cycle.
Business intelligence is a marketing confection. The graph identifies specific “components” of business intelligence. Some of the techniques necessary to obtain high value information are not included; for example, running a fake job posting designed to attract employees who currently work at the company one is subject to a business intelligence process, surveillance via mobile phones, sitting in a Starbucks watching and eavesdropping, or using analytic procedures to extract “secrets” from publicly available documents like patent applications, among others.
Business intelligence is not doing any of those things because they are [a] unethical, [b] illegal, [c] too expensive, or [d] difficult. The notion of “ethical behavior” is an interesting one. We have certain highly regarded companies taking actions which some in government agencies find improper. Nevertheless, the actions continue, not for a week or two but for decades. So maybe ethics applied to business intelligence is a non-starter. Nevertheless, certain research groups are quick to point out that unethical information gathering is not the dish served as conference luncheons.
Here are the elements or molecules of business intelligence:
- Data mining
- Data visualization
- Data preparation
- Data analytics
- Performance metrics / benchmarking
- Querying
- Reporting
- Statistical analysis
- Visual analysis
Data mining, data analytics, performance metrics / benchmarking, and statistical analysis strike me as one thing: Numerical procedures.
Now the list looks like this:
- Numerical procedures
- Data visualization
- Data preparation
- Querying
- Reporting
- Visual analysis
Let’s concatenate data visualization and visual analysis into one function: Producing charts and graphs.
Now the list looks like this:
- Producing charts and graphs
- Data preparation
- Numerical procedures
- Querying
- Reporting.
Querying, in this simplification, has moved from one of nine functions to one of five functions.
What’s up with business intelligence whipping up disciplines? Is the goal to make business intelligence more important? Is it a buzzword exercise so consultants can preach doom and sell snake oil? Is it a desire to add holiday lights and ornaments to distract people from what business intelligence is?
My hunch is that business intelligence professionals don’t want to use the words spying, surveillance, intercepts, eavesdrop, or operate like a nation state’s intelligence agency professionals.
One approach is business intelligence which seems to mean good, mathy, and valuable. The spy approach is bad and could lead to an on one Lifetime Report Card.
The fact is that one of the most important components of any intelligence operation is asking the right question. Without querying, masses of data, statistics software, and online experts with MBAs would not be able to find an online ad using Google.
Net net: The chart makes spying and surveillance into a math-centric operation. The chart fails to provide a hierarchy based on asking the right question. Will the diagram help sell business intelligence consulting and services? The scary answer is, “Absolutely.”
Stephen E Arnold, January 14, 2022
TikTok: Innocuous? Maybe Not Among Friends
January 5, 2022
Short videos. No big deal.
The data about one’s friends are a big deal. A really big deal. TikTok may be activating a network effect. “TikTok Tests Its Own Version of the Retweet with a New Repost Button” suggests that a Twitter function is chugging along. What if the “friend” is not a registered user of TikTok? Perhaps the Repost function is a way to expand a user’s social network. What can one do with such data? Building out a social graph and cross correlating those data with other information might be a high value exercise. What other uses can be made of these data a year or two down the road? That’s an interesting question to consider, particularly from the point of view of Chinese intelligence professionals.
“China Harvests Masses of Data on Western Targets, Documents Show” explains that China acquires data for strategic and tactical reasons. The write up doses not identify specific specialized software products, services, and tools. Furthermore, the price tags for surveillance expenditures seem modest. Nevertheless, there is a suggestive passage in the write up:
Highly sensitive viral trends online are reported to a 24-hour hotline maintained by the Cybersecurity administration of China (CAC), the body that oversees the country’s censorship apparatus…
What’s interesting is that China uses both software and human-intermediated systems.
Net net: Pundits and users have zero clue about China’s data collection activities in general. When it comes to specific apps and their functions on devices, users have effectively zero knowledge of the outflow of personal data which can be used to generate a profile for possible coercion. Pooh pooh-ing TikTok? Not a great idea.
Stephen E Arnold, January 5, 2022
Amazon: Lobbying Is a Component of the Model Of Course
November 23, 2021
Small news item from the trusted source Thomson Reuters. The title of the item is “Amazon Wages Secret War on Americans’ Privacy, Documents Show.” What’s interesting is that the trusted outfit has tapped into Amazon “internal documents.” These content objects reveal to the intrepid trusted real news folks that
“Amazon.com has killed or undermined privacy protections in more than three dozen bills across 25 states, as the e-commerce giant amassed a lucrative trove of personal data on millions of American consumers.”
In my lectures about this online bookstore I described some of Amazon’s public documents about its data wrangling, data stores, and data analytics capabilities. Sure, my lectures were directed at law enforcement and intelligence professionals.
How can an old person like myself using open source intelligence capture the scope, capabilities, and functionality of Amazon’s capabilities without resorting to the use of company confidential information.
If a person were to reveal company confidential information about Thomson Reuters or any of its subsidiaries, how might the Thomson Reuters “trust” brigade react to this situation?
I am no cheerleader for Amazon. I have been critical of leakers, including the cutesy Edward Snowden person.
Lobbying is an established component of many business organizations processes. Let’s think about big pharma, shall we? No, let’s not. What about those Beltway Bandits? No, let’s not.
“Trust” is an interesting concept, and I am disappointed that sensationalism and confidential information is what helps define “trust.”
Yep, real journalism. Why not rely more on open source information and good old fashioned analysis, interviews, and research? Is “too good to pass up” a factor? Blocking and tackling, right?
Stephen E Arnold, November 23, 2021
The Business Intelligence You Know Is Changing
November 11, 2021
I read “This Is the Future of Intelligence.” I have been keeping my researchers on their toes because I have an upcoming lecture about “intelligence,” not getting grades in schools which have discarded Ds and Fs. The talk is about law enforcement and investigator centric intelligence. That’s persons of interest, events, timelines, and other related topics.
This article references a research report from a mid tier consulting firm. That may ring your chimes or make you chuckle. Either way, here are three gems from the write up. I leave it to you to discern the wheat and the chaff.
How about this statement:
Prediction 1: By 2025, 10% of F500 companies will incorporate scientific methods and systematic experimentation at scale, resulting in a 50% increase in product development and business planning projects — outpacing peers.
In 36 months half of the Fortune 500 companies! I wonder how many of these outfits will be able to pay for the administrative overhead hitting this target will require. Revenue, not hand waving strike me as more important.
And this chunky Wheaties flake:
By 2026, 30% of organizations will use forms of behavioral economics and AI/ML-driven insights to nudge employees’ actions, leading to a 60% increase in desired outcomes.
If we look at bellwether outfits like Amazon and Google, I wonder if the employee push back and internal tension will deliver “desired outcomes.” What seems to be delivered are reports of management wonkiness, discrimination, and legal matters.
And finally, a sparkling Sugar Pop pellet:
By 2026, advances in computing will enable 10% of previously unsurmountable problems faced by F100 organizations to be solved by super-exponential advances in complex analytics.
I like the “previously unsurmountable problems” phrase. I don’t know what a super-exponential advance in complex analytics means. Oh, well. The mid tier experts do, I assume.
Read the list of ten findings. I had a good chuckle with a snort thrown in for good measure.
Stephen E Arnold, November 11, 2021
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