Another Data Marketplace: Amazon, Microsoft, Oracle, or Other Provider for This Construct?
August 31, 2020
The European Union is making a sharp U-turn on data privacy, we learn from MIT Technology Review’s article, “The EU Is Launching a Market for Personal Data. Here’s What That Means for Privacy.” The EU has historically protected its citizens’ online privacy with vigor, fighting tooth and nail against the commercial exploitation of private information. As of February, though, the European Commission has decided on a completely different data strategy (PDF). Reporter Anna Artyushina writes:
“The Trusts Project, the first initiative put forth by the new EU policies, will be implemented by 2022. With a €7 million [8.3 million USD] budget, it will set up a pan-European pool of personal and nonpersonal information that should become a one-stop shop for businesses and governments looking to access citizens’ information. Global technology companies will not be allowed to store or move Europeans’ data. Instead, they will be required to access it via the trusts. Citizens will collect ‘data dividends,’ which haven’t been clearly defined but could include monetary or nonmonetary payments from companies that use their personal data. With the EU’s roughly 500 million citizens poised to become data sources, the trusts will create the world’s largest data market. For citizens, this means the data created by them and about them will be held in public servers and managed by data trusts. The European Commission envisions the trusts as a way to help European businesses and governments reuse and extract value from the massive amounts of data produced across the region, and to help European citizens benefit from their information.”
It seems shifty they have yet to determine just how citizens will benefit from this data exploitation, I mean, value-extraction. There is no guarantee people will have any control over their information, and there is currently no way to opt out. This change is likely to ripple around the world, as the way EU approaches data regulation has long served as an example to other countries.
The concept of data trusts has been around since 2018, when Sir Tim Berners Lee proposed it. Such a trust could be for-profit, for a charitable cause, or simply for data storage and protection. As Artyushina notes, whether this particular trust actually protects citizens depends on the wording of its charter and the composition of its board of directors. See the article for examples of other trusts gone wrong, as well as possible solutions. Let us hope this project is set up and managed in a way that puts citizens first.
Cynthia Murrell, August 31, 2020
Forget Structured Query Language Commands? Yeah, Not Yet
August 29, 2020
One of the DarkCyber team spotted a demonstration service called NatualSQL.com. The idea is that the system will accept natural language queries of information stored in structured databases. According to the DarkCyber person, the queries launched into the natural language box were:
Sheva War with Whom
Sheva Frequency
The sparse interface sports a Content button which displays the information in the system.
How did this work?
Not well. NLP systems pose challenges still it seems.
Interesting idea but some rough edges need a bit of touch up.
Stephen E Arnold, August 29, 2020
Amazon and Toyota: Tacoma Connects to AWS
August 20, 2020
This is just a very minor story. For most people, the information reported in “Toyota, Amazon Web Services Partner On Cloud-Connected Vehicle Data” will be irrelevant. The value of the data collected by the respective firms and their partners is trivial and will not have much impact. Furthermore, any data processed within Amazon’s streaming data marketplace and made available to some of the firm’s customers will be of questionable value. That’s why I am not immediately updating my Amazon reports to include the Toyota and insurance connection.
Now to the minor announcement:
Toyota will use AWS’ services to process and analyze data “to help Toyota engineers develop, deploy, and manage the next generation of data-driven mobility services for driver and passenger safety, security, comfort, and convenience in Toyota’s cloud-connected vehicles. The MSPF and its application programming interfaces (API) will enable Toyota to use connected vehicle data to improve vehicle design and development, as well as offer new services such as rideshare, full-service lease, proactive vehicle maintenance notifications and driving behavior-based insurance.
Are there possible implications from this link up? Sure, but few people care about Amazon’s commercial, financial, and governmental services, why think about issues like:
- Value of the data to the AWS streaming data marketplace
- Link analytics related to high risk individuals or fleet owners
- Significance of the real time data to predictive analytics, maybe to insurance carriers and others?
Nope, not much of a big deal at all. Who cares? Just mash that Buy Now button and move on. Curious about how Amazon ensures data integrity in such a system? If you are, you can purchase our 50 page report about Amazon’s advanced data security services. Just write darkcyber333 at yandex dot com.
But I know first hand after two years of commentary, shopping is more fun than thinking about Amazon examined from a different viewshed.
Stephen E Arnold, August 20, 2020
Instagram: What Does Suspicious Mean at This Facebook Outfit?
August 19, 2020
DarkCyber noted what could be construed as a baby step toward adulting or a much bigger step toward Facebook obtaining more fine-grained information. “Instagram Will Make Suspicious Accounts Verify Their Identity” states:
Instagram is taking new steps to root out bots and other accounts trying to manipulate its platform. The company says it will start asking some users to verify their identities if it suspects “potential inauthentic behavior.” Instagram stresses that the new policy won’t affect most users, but that it will target accounts that seem suspicious.
It seems that “inauthentic” means “suspicious.” Okay, what is that exactly. The write up quotes an Instagram something as saying:
This includes accounts potentially engaged in coordinated inauthentic behavior, or when we see the majority of someone’s followers are in a different country to their location, or if we find signs of automation, such as bot accounts.
What addresses inauthenticity? How about this?
Under the new rules, these accounts will be asked to verify their identity by submitting a government ID. If they don’t, the company may down-rank their posts in Instagram’s feed or disable their account entirely.
When a moment of adulting or a data grab, the Facebook continues to be Facebook.
Stephen E Arnold, August 19, 2020
Data Federation: K2View Seizes Lance, Mounts Horse, and Sallies Forth
August 13, 2020
DarkCyber noted “K2View Raises $28 million to Automate Enterprise Data Unification.”
Here’s the write up’s explanation of the K2View:
K2View’s “micro-database” Fabric technology connects virtually to sources (e.g., internet of things devices, big data warehouses and data lakes, web services, and cloud apps) to organize data around segments like customers, stores, transactions, and products while storing it in secure servers and exposing it to devices, apps, and services. A graphical interface and auto-discovery feature facilitate the creation of two-way connections between app data sources and databases via microservices, or loosely coupled software systems. K2View says it leverages in-memory technology to perform transformations and continually keep target databases up to date.
The write up contains a block diagram:
Observations:
- It is difficult to determine how much manual (human) work will be required to deal with content objects not recognized by the K2View system
- What happens if the Internet connection to a data source goes down?
- What is the fall back when a microservice is not available or removed from service?
Many organizations offer solutions to disparate types of data scattered across many systems. Perhaps K2View will slay the digital windmills of silos, different types of data, and unstable connections? Silos have been part of the data landscape as long as Don Quixote has been spearing windmills.
Stephen E Arnold, August 13, 2020
After 20 Plus Years, Whoa! Surveillance by Big Tech
August 10, 2020
DarkCyber has noted a flurry of write ups expressing surprise, rage, indignation, and blusterification at the idea of a commercial company collecting data. Hello, services are free for a basic reason: Making money. Part of making money is to have something that other companies and organizations will purchase. A good example is personal information about users of free services. The way big companies work is that there is a constant pressure to find new ways to generate money. Thus, there are data sucking apps; there are advertisements and more advertisements; there are subscriptions which lock in revenue while providing an Amazon-style we know a lot about those who shop on Amazon; and there are many ornaments on these methods.
I got a kick out of “Silicon Valley’s Vast Data Collection Should Worry You More Than TikTok.” We know the story well. Commercial firms in the US gather data and license it, often to marketing firms and to other organizations. After two decades of blissful ignorance a devoted band of “real” journalists are now probing the core business model of many technology centric companies.
Give me a break. We are talking decades of business processes designed to generate useful reports from flows of actions by individuals. In some countries, the government performs this task. In others, commercial enterprises do the work and license the normalized data to governments.
This passage from the write up tickled my funny bone:
And none of this is unreasonable. We should be worried about private companies and governments potentially collecting data on millions of unsuspecting people and censoring content they don’t like. But those based in China represent just a sliver of that threat.
Yep, the old “woulda, coulda, shoulda” ploy. May I remind you, gentle reader, that we are decades into the automation of data about the actions of individuals. These are the happy and often ignorant humanoids who download apps, run queries, click on videos, and send personal message while leaving a data trail a foot deep and a mile wide.
And now the need for something?
And data collection is not a technical and economic issue. Nope. Data collection is politics; for example:
TikTok’s critics might point to the increasingly scary behavior of China’s government as to why Chinese control of information is particularly alarming. They’re right about the behavior, but they curiously ignore the fact that the United States itself is currently governed by a far-right demagogue with his own concentration camps and authoritarian repression, and that the party behind him, which aligns entirely with his politics, reliably cycles into power at least once every eight years.
What’s the fix? Well, “oppose it all.”
Where were the regulators, the users, and the competitors 20 years ago? Probably in grade school, blissfully unaware that those handheld gadgets would become more important than other activities. Okay, adult thumbtypers, your outrage is interesting. Step back, and perhaps you can see why the howls of outrage, the references to evil forms of government, and the horrors of toting around a device that usually provides real time documentation of one’s actions as a bad thing.
But after 20 years, is it surprising that personal data actions are captured, analyzed, and used to provide more data “stuff” to consume? As I said, its been 20 years with no lessening of the processes. Complain to your parents. Maybe they dropped the ball? Commercial enterprises and governments are like beavers. And beavers do what beavers do.
Stephen E Arnold, August 10, 2020
Quantexa: A Better Way to Nail a Money Launderer?
July 29, 2020
We noted the Techcrunch article “Quantexa Raises $64.7M to Bring Big Data Intelligence to Risk Analysis and Investigations.” There were a number of interesting statements or factoids in the write up; for example:
Altogether, Quantexa has “thousands of users” across 70+ countries, it said, with additional large enterprises, including Standard Chartered, OFX and Dunn & Bradstreet.
We also circled in true blue marker this passage:
As an example, typically, an investigation needs to do significantly more than just track the activity of one individual or one shell company, and you need to seek out the most unlikely connections between a number of actions in order to build up an accurate picture. When you think about it, trying to identify, track, shut down and catch a large money launderer (a typical use case for Quantexa’s software) is a classic big data problem.
And lastly:
Marria [the founder] says that it has a few key differentiators from these. First is how its software works at scale: “It comes back to entity resolution that [calculations] can be done in real time and at batch,” he said. “And this is a platform, software that is easily deployed and configured at a much lower total cost of ownership. It is tech and that’s quite important in the current climate.”
Some “real time” systems require time consuming and often elaborate configuration to produce useful outputs. The buzzwords take precedence over the nuts and bolts of installing, herding data, and tuning the outputs of this type of system.
Worth monitoring how the company’s approach moves forward.
Stephen E Arnold, July 29, 2020
Oracle and Blockchain
July 28, 2020
Amidst the angst about US big technology companies, Rona, and Intel’s management floundering, Oracle blockchain is easy to overlook. “Oracle Updates Blockchain Platform Cloud Service.” The title alone invokes the image of Amazon’s blockchain platform and its associated moving parts.
The write up focuses on Oracle as if the Amazon and other options do not exist. But the parallels with Amazon’s blockchain services are clearly articulated. The article reports:
Blockchain Platform Cloud Service features stronger access controls for sharing confidential information, greater decentralization capabilities for blockchain consortiums, and stronger audibility when rich history database feature is used in conjunction with Oracle Database Blockchain Tables.
Even more Amazon envy seems to have influenced this “new” feature:
Oracle Cloud Infrastructure Availability Domains (and in the regions with a single Availability Domain, three Fault Domains) to provide stronger resilience and recoverability, with the SLA for the Enterprise SKUs of at least 99.95%.
The line up of services strikes me as having been developed after reading Amazon’s blockchain documentation; for example:
- On demand storage
- Spiffed up access controls
- Workflow functions.
There is one difference, however. It appears that Oracle wants to tackle Amazon blockchain at a weak point: Price. Oracle is not likely to be significantly cheaper than AWS blockchain. Oracle wants to make its pricing more or less understandable to a prospect.
Will clarity allow Oracle to compete with Amazon blockchain?
After losing Amazon as a customer and watching the online book store pump out blockchain inventions for several years, Oracle hopes its approach will prevail or at least catch up with the Bezos bulldozer.
Stephen E Arnold, July 28, 2020
TileDB Developing a Solution to Database Headaches
July 27, 2020
Developers at TileDB are working on a solution to the many problems traditional and NoSQL databases create, and now they have secured more funding to help them complete their platform. The company’s blog reports, “TileDB Closes $15M Series A for Industry’s First Universal Data Engine.” The funding round is led by Two Bear Capital, whose managing partner will be joining TileDB’s board of directors. The company’s CEO, Stavros Papadopoulos, writes:
“The Series A financing comes after TileDB was chosen by customers who experienced two key pains: scalability for complex data and deployment. Whole-genome population data, single-cell gene data, spatio-temporal satellite imagery, and asset-trading data all share multi-dimensional structures that are poorly handled by monolithic databases, tables, and legacy file formats. Newer computational frameworks evolved to offer ‘pluggable storage’ but that forces another part of the stack to deal with data management. As a result, organizations waste resources on managing a sea of files and optimizing storage performance, tasks traditionally done by the database. Moreover, developers and data scientists are spending excessive time in data engineering and deployment, instead of actual analysis and collaboration. …
“We invented a database that focuses on universal storage and data management rather than the compute layer, which we’ve instead made ‘pluggable.’ We cleared the path for analytics professionals and data scientists by taking over the messiest parts of data management, such as optimized storage for all data types on numerous backends, data versioning, metadata, access control within or outside organizational boundaries, and logging.”
So with this tool, developers will be freed from tedious manual steps, leaving more time to innovate and draw conclusions from their complex data. TileDB has also developed APIs to facilitate integration with tools like Spark, Dask, MariaDB and PrestoDB, while TileDB Cloud enables easy, secure sharing and scalability. See the write-up for praise from excited customers-to-be, or check out the company’s website. Readers can also access the open-source TileDB Embedded storage engine on Github. Founded in 2017, TileDB is based in Cambridge, Massachusetts.
Cynthia Murrell, July 27, 2020
IHS Markit Data Lake “Catalog”
July 14, 2020
One of the DarkCyber research team spotted this product announcement from IHS, a diversified information company: “IHS Markit’s New Data Lake Delivers Over 1,000 Datsets in an Integrated Catalogued Platform.” The article states:
The cloud-based platform stores, catalogues, and governs access to structured and unstructured data. Data Lake solutions include access to over 1,000 proprietary data assets, which will be expanded over time, as well as a technology platform allowing clients to manage their own data. The IHS Markit Data Lake Catalogue offers robust search and exploration capabilities, accessed via a standardized taxonomy, across datasets from the financial services, transportation and energy sectors.
The idea is consistently organized information. Queries can run across the content to which the customer has access.
Similar services are available from other companies; for example, Oracle BlueKai.
One question which comes up is, “What exactly are the data on offer?” Another is, “How much does it cost to use the service?”
Let’s tackle the first question: Scope.
None of the aggregators make it easy to scan a list of datasets, click on an item, and get a useful synopsis of the content, content elements, number of items in the dataset, update frequency (annual, monthly, weekly, near real time), and the cost method applicable to a particular “standard” query.
A search of Bing and Google reveals the name of particular sets of data; for example, Carfax. However, getting answers to the scope question can require direct interaction with the company. Some aggregators operate in a similar manner.
The second question: Cost?
The answer to the cost question is a tricky one. The data aggregators have adopted a set or a cluster of pricing scenarios. It is up to the customer to look at the disclosed data and do some figuring. In DarkCyber’s experience, the data aggregators know much more about what content process, functions or operations generate the maximum profit for the vendor. The customer does not have this insight. Only through use of the system, analyzing the invoices, and paying them is it possible to get a grip on costs.
DarkCyber’s view is that data marketplaces are vulnerable to disruption. With a growing demand for a wide range of information some potential customers want answers before signing a contract and outputting big bucks.
Aggregators are a participant in what DarkCyber calls “professional publishing.” The key to this sector is mystery and a reluctance to spell out exact answers to important questions.
What company is poised to disrupt the data aggregation business? Is it the small scale specialist like the firms pursued relentlessly by “real” journalists seeking a story about violations of privacy? Is it a giant company casting about for a new source of revenue and, therefore, is easily overlooked. Aggregation is not exactly exciting for many people.
DarkCyber does not know. One thing seems highly likely: Professional publishing data aggregation sector is likely to face competitive pressure in the months ahead.
Some customers may be fed up with the secrecy and lack of clarity and entrepreneurs will spot the opportunity and move forward. Rich innovators will just buy the vendors and move in new directions.
Stephen E Arnold, July 14, 2020
-
- Subscribe to Beyond Search
Feature archive
News archive
-
