The Obvious: Business Intelligence Tools May Need Clarity

August 14, 2018

Artificial intelligence and business have been a natural pair since the moment we began speculating about this technology. However, we are currently in a sort of golden age of AI for business (or drowning in a swamp of it, depending who you ask) and we could all use a little help sorting through the options. That’s why a recent Data Science Central story “A Comparative Analysis of Top 6 BI and Data Visualization Tools in 2018” seemed so relevant.

According to the story:

“It is often hard to separate the facts from fiction when evaluating various business intelligence (BI) tools, as every BI vendor markets their product as the only “best” solution, often flooding the Internet with biased reviews. If you want to understand the functional product value, avoid the hype and useless clicking through endless pages of partial reviews, you’ve come to the right place.”

This is a very important breakdown and it goes over some really compelling programs, depending on your needs. This seems to be a trend in the industry as we become awash in BI choices. Recently, we also discovered a valuable contrast looking at augmented analytics versus business intelligence tools. What seems obvious is that developers are trying to provide point and click math insight and expertise to individuals who may lack a firm foundation in evaluating data quality, statistics, and other disciplines. No, majoring in medieval literature is not what is needed to make sense of data. To be fair, some find art in proofs.

Insight from slick interfaces? Maybe.

Patrick Roland, August 14, 2018

Amazon and Its Unrest Prediction

July 24, 2018

The Guardian, a “real” newspaper, published “Why the Amazon Boss’s Warning of No-Deal Brexit Unrest Rings Hollow.” The write up is a response to an Amazon executive’s prediction that muffing the Brexit trade deal bunny will lead to “civil unrest.” My interest is not the fate of the UK. I am, however, intrigued by an Amazon executive making a statement similar to those offered by individuals with access to intelligence centric next generation information access systems. (If you want additional information about NGIAs, check out CyberOSINT.)

The question which crossed my mind when I heard about the prediction was:

Does Amazon have access to an NGIA system similar to an IBM Analyst Notebook or a Palantir Gotham?

If the answer is, “No,” then I asked myself:

Does Amazon have its own intelligence analysis system?

From my vantage point in rural Kentucky, I have zero first hand information about Amazon and its possible intelligence capabilities.

It is indeed interesting to have this prediction emitted from what is usually a quite secretive outfit. My instincts suggest that Amazon does have an active intelligence system. This prediction may be a planned or unanticipated factoid by an Amazon executive.

Amazon does have some interesting capabilities, new functions which have been patented, and a number of vendors of policeware and intelware who use the Amazon AWS plumbing.

My takeaway from the prediction and the Guardian type coverage suggests that a closer, more informed look at what Amazon does to inform its executives of possible developments is warranted.

Stephen E Arnold, July 24, 2018

Business Intelligence: What Is Hot? What Is Not?

July 16, 2018

I read “Where Business Intelligence is Delivering Value in 2018.” The write up summarizes principal findings from a study conducted by Dresner Advisory Services, an outfit with which I am not familiar. I suggest you scan the summary in Cloud Tweaks and then, if you find the data interesting, chase after the Dresner outfit. My hunch is that the sales professionals will respond to your query.

Several items warranted my uncapping my trusty pink marker and circling an item of information.

First, I noticed a chart called Technologies and Initiatives Strategic to Business Intelligence. The chart presents data about 36 “technologies.” I noticed that “enterprise search” did not make the list. I did note that cognitive business intelligence, artificial intelligence, t4ext analytics, and natural language analytics did. If I were generous to a fault, I would say, “These Dresner analysts are covering enterprise search, just taking the Tinker Toy approach by naming areas of technologies.” However, I am not feeling generous, and I find it difficult to believe that Dresner or any other knowledge worker can do “work” without being able to find a file, data, look up a factoid, or perform even the most rudimentary type of research without using search. The omission of this category is foundational, and I am not sure I have much confidence in the other data arrayed in the report.

Second, I don’t know what “data storytelling” is. I suppose (and I am making a wild and crazy guess here) that a person who has some understanding of the source data, the algorithmic methods used to produce output, and the time to think about the likely accuracy of the output creates a narrative. For example, I have been in a recent meeting with the president of a high technology company who said, “We have talked to our customers, and we know we have to create our own system.” Obviously the fellow knows his customers, essentially government agencies. The customers (apparently most of them) want an alternative, and realizes change is necessary. The actual story based on my knowledge of the company, the product and service he delivers, and the government agencies’ budget constraints. The “real story” boils down to: “Deliver a cheaper product or you will lose the contract.” Stories, like those from teenagers who lose their homework, often do not reflect reality. What’s astounding is that data story telling is number eight on the hit parade of initiatives strategic to business intelligence. I was indeed surprised. But governance made the list as did governance. What the heck is governance?

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Business Intelligence Search: Not There Yet

February 20, 2018

Business intelligence applications are indispensable for modern companies, especially if they are focused at being the top of their industry. Apparently one common feature still eludes BI application developers: search. How can something so basic and readily available through open source technology be difficult to master? ZDNet reviews Forrester’s breakdown of the BI landscape in the article, “Make BI Applications More Intuitive With Search Like GUI.”

BI applications are kept relativity simple with a mouse-based user interface, so end user training is kept to a minimum and adoption into systems is easier. One item of concern is that few decision-makers actually access the data directly and rely on their business analysts and other team members to provide them information. BI applications are not so simple, however, and the end users need to be knowledgeable in the data sources and metadata.

Thank goodness that there is a GUI for BI applications and it has natural language processing:

“This has largely come true with natural language processing (NLP) and natural language generation (NLG) technologies. Users can now ask a question in a natural language (where NLP translates a question to a query, aka text-to-query) and get an answer via a programmatically generated narrative based on the result set returned by the query. The NLG narratives are especially effective when displayed side by side with a visualization. In addition to NLP and NLG capabilities built into BI tools, some BI providers are also creating chatbots as separate applications. These can allow non-technical BI users to ask questions and receive dynamically generated data visualizations and written highlights without knowing anything about the underlying data structures or metadata.”

The question remains if the search application will be decent and usable on newer BI interfaces. Only time and user feedback will tell.

Whitney Grace, February 20, 2018

AI Will Be 2018s Biggest Tech Topic

February 20, 2018

Seems like some algorithm should have predicted this a long time ago, but our best bet is that AI leads the way in most important tech topics of the new year. We are not alone. Datanami recently penned an article, “What Will AI Bring in 2018? Experts Sound Off.”

According to the story:

Artificial intelligence and machine learning are often misunderstood and misused terms. Many startups and larger technology companies attempt to boost their appeal by forcing an association with these phrases. Well, the buzz will have to stop in 2018…This will be the year we begin to demand substance to justify claims of anything that’s capable of using data to predict any outcome of any relevance for business, IT or security. While 2018 will not be the year when AI capabilities mature to match human skills and capacity, AI using machine learning will increasingly help organizations make decisions on massive amounts of data that otherwise would be difficult for us to make sense of.

This comes as no surprise to us. AI has been cracking mysteries left and right lately and is finally getting down to seriously important work. Take, for example, how AI is helping solve the opioid crisis. AI will be 2018’s big story and it couldn’t come at a better time for us.

Patrick Roland, February 20, 2018

Financial Research: Rumblings Get Louder

February 8, 2018

Regulations are having causing small tremors in the high altitude research business. I read “U.S. Asset Managers Shake Up Equity research as Banks Cut Back.” The write up offered several pieces of intelligence which might be considered “real” news.

First, outfits with money to invest and “churn” are hiring people who know specific things; for example, a former product manager at a company manufacturing gear related to artificial intelligence. No MBA needed was the take away for me.

Second, big money outfits have cut back on buying research. According to the article, one big money executive stopped buying bank research and learned “that he could live without most of it.”

Third, I highlighted this headache inducing statement for the providers of high end research:

Major global investment banks slashed their equity research budgets from a peak of $8.2 billion in 2008 to $3.4 billion in 2017, according to Frost Consulting. McKinsey projects the top 10 banks will cut those budgets by another 30 percent in the near term…

My question, “What happens to the Investext business?” Another one: “What acquisitions will big money companies make in order to deal with the changes in research?”

Worth watching.

Stephen E Arnold, February 8, 2018

Business Intelligence: A List of 238 Firms

November 30, 2017

Need a list of “fermium” business intelligence tools. That’s no typo. That is the word on page 2 of Top Business intelligence Solutions. Looking past the misspelling, the write up from Predictive Analytics Today presents a listing in no particular order of more than 200 business intelligence tools. The text is accompanied by little boxes with scores in them like this:

image

The list was a lot of work. The names of companies are collected in these major categories:

  1. Free cloud business intelligence solutions
  2. Free open source business intelligence tools
  3. Free proprietary business intelligence tools
  4. Open source commercial business intelligence tools
  5. Top business intelligence companies
  6. Free extract, transform and load software
  7. Top extract, transform and load software
  8. Cloud SaaS on demand business intelligence solutions
  9. Freemium cloud business intelligence solutions
  10. Open source balanced scorecard software
  11. Top balanced scorecard software
  12. Open source and free dashboard software
  13. Top dashboard software
  14. Embedded business software
  15. Open source and free unified modeling language tools
  16. Open source and free business process management tools

What I found interesting about the list was:

  • For fee vendors appear in “free” categories; for example, IBM Watson and Microsoft
  • Many of the vendors have versions of their software for the intelligence and law enforcement community. Most of these versions of the companies with specialized tools are not free
  • None of the specialist firms which I track appear on the list; for example, BAE Systems, a company whose tools rival those of many of the other firms on the list.
  • The vendor Attivio was left out. This surprised me because Attivio pitches itself as a business intelligence solution and it has a tie up with Tibco, a product dependent in part on software created by the founders of Recorded Future, a company which I track because it has robust intelligence capabilities embodied in its products and services.
  • There are curious omissions. One important one is Palantir, whose Gotham product powers a number of commercial business intelligence applications like those from Thomson Reuters’ financial product line.
  • Many vendors appear in multiple categories. This left me confused. For major vendors it would have been helpful to provide the company name “IBM” with a summary of what the company offers as free, freemium, open source, proprietary, etc.

Nevertheless, the listing is interesting for those wanting to track some of the vendors pursuing the business intelligence sector. To learn about companies not on the Predictive Analytics’ list, follow DarkCyber, my weekly video program. Each week, I profile intelligence companies which are often off the radar of some commercial procurement teams. That’s unfortunate because the firms I follow are indeed cutting edge when it comes to real life intelligence analysis. Most of these products, in my experience, cost money either for engineering, training, support, or add ons.

You can find the video by navigating to this link or running a query for Arnold Dark Cyber on Google.com or on Googlevideo.com.

Stephen E Arnold, November 30, 2017

Analytics Tips on a Budget

November 23, 2017

Self-service analytics is another way to say “analytics on a budget.”  Many organizations, especially non-profits, do not have the funds to invest in a big data plan and technology, so they decide to take the task on themselves.  With the right person behind the project, self-service analytics is a great way to save a few bucks.  IT Pro Portal shares some ways how to improve on an analytics project in, “Three Rules For Adopting Self-Service Analytics.”  Another benefit to self-service analytics is that theoretically anyone in the organization can make use of the data and find some creative outlet for it.  The tips come with the warning label:

Any adoption of new technology requires a careful planning, consultation, and setup process to be successful: it must be comprehensive without being too time-consuming, and designed to meet the specific goals of your business end-users. Accordingly, there’s no one-size-fits-all approach: each business will need to consider its specific technological, operational and commercial requirements before they begin.

What are the three tips?

  1. Define your business requirements
  2. Collaborate and integrate
  3. Create and implement a data governance policy

All I can say to this is, duh!  These are standard tips that can be applied, not only for self-service analytics but also BI plans and any IT plan.  Maybe there are a few tips directly geared at the analytics field but stick to fewer listicles and more practical handbooks.  Was this a refined form of clickbait?

Whitney Grace, November 23, 2017

Solve BI Woes with This Listicle

November 20, 2017

Business intelligence is a key component in any business that wants to be competitive, turn a profit, and make themselves a known entity.  The problem, however, is betting your business intelligence plan off the ground.  CIO shares the top, “Three Reasons Your Business Intelligence Adoption Has Stalled.”  Old-fashioned BI plans relied heavily on putting technology at the forefront and having a dedicated staff to manage it.  The traditional model has changed because everyone in an organization can have access to the same type of technology that once was specialized.

The problem with implementing a BI plan is more than likely than the company culture.  The first problem is that employees (and everyone) are resistant to change.  Forcing employees to use new technology not only creates conflict, but there is also the problem with data literacy.  It usually takes a lot of training sessions to get everyone’s skills on par.

Another problem is that some companies rely too heavily on their gut instinct that confirmed data:

BI leaders spend a disproportionate amount of time trying to convince instinct-based decision-makers that analytic insight beats intuition. Unfortunately, this rarely changes deep-rooted beliefs and has little-to-no impact on the use of BI. Consequently, BI teams are better served engaging leaders who understand the value of analytics and are willing and able to influence business process change. Top-down support from organizational leaders to challenge the status quo, and push for business process transformation, is mandatory for success. It will quickly become evident to senior leaders which of their key decision-makers are furthering – or hindering – the organization’s BI and analytic adoption goals.

The third problem is that organizations implement a BI plan, usually around an IT project, and once it is rolled out and on the go, nothing else is done with it.  Companies think that once a BI plan is in place, then it will not need to evolve in the future.  A fluid mentality, rather than a check-box one is how organizations will have successful BI deployments.

Whitney Grace, November 20, 2017

Silobreaker Digs Deeper into Dark Web

November 9, 2017

The Dark Web is small, unmonitored part of the Internet.  While the Dark Web seems untraceable and unsearchable, many tech companies are making strides documenting it.  Silobreaker is one of the companies and they announced a partnership with Flashpoint to take on the Dark Web: “Silobreaker Expands Its Data Coverage To Deep And Dark Web By Teaming Up With Flashpoint.”  Flashpoint is a leading provider of business risk intelligence technology and they focus on uncovering Dark Web information.

Flashpoint recently released version four of their business risk intelligence API.  Along with the newest release, Silobreaker and Flashpoints’ team up means that more of their clients will be able to predict, detect, and resolve unstructured data into actionable intelligence.

How will Silobreaker and Flashpoint work together?

Flashpoint’s data is being ingested by Silobreaker’s platform, where it is indexed and fully integrated for use across all analytical tools, visualizations and workflow features. When correlated with Silobreaker’s open source data, this combination empowers customers to move seamlessly between the two data-sets in a single application, expanding their analyses to include both.

The only downside is in order to take advantage of the team up, their clients must have licenses to both companies.  Maybe they will offer a bundle deal if you ask nicely.

Whitney Grace, November 9, 2017

 

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