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

 

A Flashing Way to Find Business Risks

November 8, 2017

Business intelligence involves many factors that range from enterprise systems to big data business analytics.  Another aspect is determining the risk of business decisions.  While a piece of software does not exist that can accurately predict the future, technology companies have come close.  Programmable Web published the article, “Flashpoint Launches V4 Of Its Business Risk Intelligence API” that describes one company’s newest endeavors in business risk intelligence.

Flashpoint’s business risk intelligence API is officially on its fourth version.  Dubbed Flashpoint API 4, the software provides a set of cybersecurity tools and the newest version includes a dataset for Risk Intelligence Observables (RIOs).  RIOs dig deeper than past indicators in specified activities to deliver secure insights.

The Flashpoint API aims to deliver near to real-time access to its security services. Because of RESTful API access, Flashpoint technology is available to entry-level users and enterprises alike. Through the API, users can search across Finished Intelligence, Deep & Dark Web data, and RIOs. A key component of Flashpoint’s strategy is context surrounding threats, and the API’s customization options allow users to define and address context to suit specific needs. Contact the Flashpoint team for more information.

Perhaps the most impressive thing about version four’s release is the partner community.  These include ThreatConnect, ThreatQuotient, Silobreaker, and Anomali.  These four companies are part of Flashpoint’s Strategic Partner Network and all have the goal to help companies detect cybercrime and other threats.

Whitney Grace, November 8, 2017

Report Assesses Todays Voice Assistant Landscape

November 2, 2017

Having observed the recent boom in AI-powered voice-assistant products, Business Insider’s research service, BI Intelligence, has conducted a study on the issue. The site promotes their findings in their preview, “The Voice Assistant Landscape Report.” Writer Jessica Smith begins with an overview of recent developments: AI has become more accurate; mobile networks are more powerful; and smart appliances (aka the “internet of things”) supply more opportunities for voice-command control. By 2015, she reports, 65% of those with smartphones in the U.S. used voice assistants with those devices. Also, sales of Google Home and Amazon Echo are expected to triple this year, to 24.5 million units. Still, we’re told there remain significant obstacles, both social and technical, to widespread adoption just yet.

Smith shares some findings from the report. Among them:

Technological advances are making voice assistants more capable. These improvements fall into two categories: improvements in AI, specifically natural language processing (NLP) and machine learning; and gains in computing and telecommunications infrastructure, like more powerful smartphones, better cellular networks, and faster cloud computing.

Changes in consumer behavior and habits are also leading to greater adoption. Chief among these are increased overall awareness and a higher level of comfort demonstrated by younger consumers.

The voice assistant landscape is divided between smartphone- and speaker-based assistants. These distinctions, while important now, will lose relevance in the long run as more assistants can be used on both kinds of devices. The primary players in the space are Apple’s Siri, Microsoft’s Cortana, Google Assistant, Amazon’s Alexa, and Samsung’s Viv.

Stakes in the competition for dominance in the voice assistant market are high. As each assistant becomes more interconnected with an ecosystem of devices that it can control, more popular platforms will have a sizable advantage.

Naturally, the article concludes by telling us how to get our hands on the full report. You could invest in the BI Intelligence “All-Access” pass if you are really, really into research reports. Or, you could just purchase and download this particular report here for $495.

Cynthia Murrell, November 2, 2017

 

The Narrowing App Market

September 29, 2017

If you are thinking of going into app development, first take a gander at this write-up; Business Insider reports, “Half of Digital Media Time Is Spent in Five Apps.” Citing comScore’s 2017 US Mobile App Report , writer Laurie Beaver tells us:

Users spend 90% of their mobile app time in their top five apps, making up 51% of total digital time spent. Perhaps more alarming is that half of the time spent on smartphones is within just one app. That drops dramatically to 18% of time for the second most used app. This suggests that unless a brand’s or business’ app is the first or second most used (most likely Facebook- or Google-owned), it’s unlikely to get any meaningful share of users’ attention.

There are a few reasons for developers to take heart—the number of app downloads is picking up, and users have become more willing to allow push notifications. Most importantly, perhaps, is that users are making in-app purchases; that is where most apps make their money. Beaver continues:

Nevertheless, the report shows the astonishing influence Facebook and Google have over how US mobile app users spend their time. And given the increasingly large share the top five apps have, it’s likely to only become more difficult for brands and publishers to receive any share of users’ time. Alternate app experiences such as Apple’s iMessage apps, Google’s Instant Apps, and Facebook Messenger’s Instant Games could provide brands and publishers with new avenues to reach consumers where they’re spending their time. While these services are nascent, they do provide a promising option for businesses moving forward.

We’re reminded that apps have gained ground over browsers, and are now the main way folks get online. However, the trends toward app consolidation and app abandonment may lead to a “post-app” future. Never fear, though—Business Insider’s research service, BI Intelligence, offers a report titled “The End of Apps” ($495) that could help businesses and developers prepare for the future. Founded in 2007, Business Insider is headquartered in New York City.

Cynthia Murrell, September 29, 2017

Why the Future of Computing Lies in Natural Language Processing

September 26, 2017

In a blog post, EasyAsk declares, “Cognitive Computing, Natural Language & AI: Game Changers.”  We must keep in mind that the “cognitive eCommerce” company does have a natural language search engine to sell, so they are a little biased. Still, writer and CEO Craig Bassin make some good points. He begins by citing research firm Gartner’s assessment that natural-language query “will dramatically change human-computer interaction.” After throwing in a couple amusing videos, Bassin examines the role of natural language in two areas of business, business intelligence (BI) and customer relationship management (CRM). He writes:

That shift [to natural language and cognitive computing] enables two things. First, it enables users to ask a computer questions the same way they’d ask an associate, or co-worker. Second, it enables the computer to actually answer the question. That’s the game changer. The difference is a robust Natural Language Linguistic Engine. Let’s go back to the examples above for a reexamination of our questions. For BI, what if there was an app that looked beyond the dashboards into the data to answer ah-hoc questions? Instead of waiting days for a report to be generated, you could have it on the fly – right at your fingertips. For CRM, what if that road warrior could ask and answer questions about the current status across prospects in a specific region to deduce where his/her time would be best spent? Gartner and Forrester see the shift happening. In Gartner’s Magic Quadrant Report for Business Intelligence and Analytics Platforms [PDF], strategic planning assumptions incorporate the use of natural language. It may sound like a pipe dream now, but this is the future.

Naturally, readers can find natural-language goodness in EasyAsk’s platform which, to be fair, has been building their cognitive computing tech for years now. Businesses looking for a more sophisticated search solution would do well to check them out—along with their competition.  Based in Burlington, Mass., EasyAsk also maintains their European office in Berkshire, UK. The company was founded in 2000 and was acquired by Progress Software in 2005.

Cynthia Murrell, September 26, 2017

Analytics for the Non-Tech Savvy

August 18, 2017

I regularly encounter people who say they are too dumb to understand technology. When people tell themselves this, they are hindering their learning ability and are unable to adapt to a society that growing more dependent on mobile devices, the Internet, and instantaneous information.  This is especially harmful for business entrepreneurs.  The Next Web explains, “How Business Intelligence Can Help Non-Techies Use Data Analytics.”

The article starts with the statement that business intelligence is changing in a manner equivalent to how Windows 95 made computers more accessible to ordinary people.  The technology gatekeeper is being removed.  Proprietary software and licenses are expensive, but cloud computing and other endeavors are driving the costs down.

Voice interaction is another way BI is coming to the masses:

Semantic intelligence-powered voice recognition is simply the next logical step in how we interact with technology. Already, interfaces like Apple’s Siri, Amazon Alexa and Google Assistant are letting us query and interact with vast amounts of information simply by talking. Although these consumer-level tools aren’t designed for BI, there are plenty of new voice interfaces on the way that are radically simplifying how we query, analyze, process, and understand complex data.

 

One important component here is the idea of the “chatbot,” a software agent that acts as an automated guide and interface between your voice and your data. Chatbots are being engineered to help users identify data and guide them into getting the analysis and insight they need.

I see this as the smart people are making their technology available to the rest of us and it could augment or even improve businesses.  We are on the threshold of this technology becoming commonplace, but does it have practicality attached to it?  Many products and services are common place, but it they only have flashing lights and whistles what good are they?

Whitney Grace, August 18, 2017

Big Datas Big Leap

August 11, 2017

One of the biggest problems of players of Business Intelligence through Big Data is its adoption. While companies with deep pockets are still scratching their heads, the industry will take off only when small and medium sized business adopt it.

According to an article published by Stats and Bots titled Open Source Business Intelligence, the author says:

Open source BI allows businesses to install the core platform on any system in their environment for free. Hundreds of developers are continuously improving and expanding these products. You can benefit from regular updates, or even customize BI software by modifying or extending source code to meet your company’s specific needs.

Open source tools for adopting BI solutions will go a long way in establishing the industry. The biggest stumbling block in adopting these solutions is cost of implementation. Thus, BI companies now are offering their tools free of cost and as open source.

Google, in order to capture the mobile OS market, offered its flagship OS Android free of cost to OEM and third parties. This enabled the company to create an ecosystem around the OS that is worth billions of dollars now. Open Source is the way to go it seems.

Vishal Ingole, August 11, 2017

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