Business Intelligence Take on the Direction of Media
October 7, 2016
The article on Business Insider titled The Top 7 Predictions For the Future of Media offers a long gaze into the crystal ball. With significant research over the past six years including interviews with key industry players, the article posits that the future is clear for those willing to sit through the IGNITION Conference presentation put together by BI’s co-founder and CEO Henry Blodget. The article sums up the current state of uncertainty in media,
Users are moving away from desktop and toward mobile. Social media referrals are overtaking search. Consumers are cutting their cords and saying goodbye to traditional pay-TV. Messaging apps are threatening email. And smart devices are starting to connect everything around us. These changes in trends can disrupt our businesses, our portfolios, and even our lives. But they don’t have to…Those who are well informed and well prepared don’t see innovation as a threat; they see it as an opportunity.
The article overviews some of the major takeaways from the presentation such as: Newspapers will soon be joined by TV networks in their frustrating battle for relevance. The article also mentions that the much-discussed ad blocking crisis will “resolve itself,” with the caustic note that we should all be “careful what [we] wish for.” Not much interest in finding information however. The full report is available through BI for free after signing up.
Chelsea Kerwin, October 7, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Semantify Secures Second Funding Round
August 4, 2016
Data-management firm Semantify has secured more funding, we learn from “KGC Capital Invests in Semantify, Leaders in Cognitive Discovery and Analytics” at Benzinga. The write-up tells us primary investor KGC Capital was joined by KDWC Venture Fund and Bridge Investments in making the investment, as well as by existing investors (including its founder, Vishy Dasari.) The funds from this Series A funding round will be used to address increased delivery, distribution, and packaging needs.
The press release describes Semantify’s platform:
“Semantify automates connecting information in real time from multiple silos, and empowers non-technical users to independently gain relevant, contextual, and actionable insights using a free form and friction-free query interface, across both structured and unstructured content. With Semantify, there would be no need to depend on data experts to code queries and blend, curate, index and prepare data or to replicate data in a new database. A new generation self-service enterprise Ad-hoc discovery and analytics platform, it combines natural language processing (NLP), machine learning and advanced semantic modeling capabilities, in a single seamless proprietary platform. This makes it a pioneer in democratization of independent, on demand information access to potentially hundreds of millions of users in the enterprise and e-commerce world.”
Semantify cites their “fundamentally unique” approach to developing data-management technology as the force behind their rapid deployment cycles, low maintenance needs, and lowered costs. Formerly based in Delaware, the company is moving their headquarters to Chicago (where their investors are based). Semantify was founded in 2008. The company is also hiring; their About page declares, toward the bottom: “Growing fast. We need people;” as of this writing, they are seeking database/ BI experts, QA specialists, data scientists & knowledge modelers, business analysts, program & project managers, and team leads.
Cynthia Murrell, August 4, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Data Wrangling Market Is Self-Aware and Growing, Study Finds
June 20, 2016
The article titled Self-Service Data Prep is the Next Big Thing for BI on Datanami digs into the quickly growing data preparation industry by reviewing the Dresner Advisory Services study. The article provides a list of the major insights from the study and paints a vivid picture of the current circumstances. Most companies often perform end-user data preparation, but only a small percentage (12%) find themselves to be proficient in the area. The article states,
“Data preparation is often challenging, with many organizations lacking the technical resources to devote to comprehensive data preparation. Choosing the right self-service data preparation software is an important step…Usability features, such as the ability to build/execute data transformation scripts without requiring technical expertise or programming skills, were considered “critical” or “very important” features by over 60% of respondents. As big data becomes decentralized and integrated into multiple facets of an organization, users of all abilities need to be able to wrangle data themselves.”
90% of respondents agreed on the importance of two key features: the capacity to aggregate and group data, and a straightforward interface for implementing structure on raw data. Trifacta earned the top vendor ranking of just under 30 options for the second year in a row. The article concludes by suggesting that many users are already aware that data preparation is not an independent activity, and data prep software must be integrated with other resources for success.
Chelsea Kerwin, June 20, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Tips on How to Make the Most of Big Data (While Spending the Least)
April 13, 2016
The article titled The 10 Commandments of Business Intelligence in Big Data on Datanami offers wisdom written on USB sticks instead of stone tablets. In the Business Intelligence arena, apparently moral guidance can take a backseat to Big Data cost-savings. Suggestions include: Don’t move Big Data unless you must, try to leverage your existing security system, and engage in extensive data visualization sharing (think Github). The article explains the importance of avoiding certain price-gauging traps,
“When done right, [Big Data] can be extremely cost effective… That said…some BI applications charge users by the gigabyte… It’s totally common to have geometric, exponential, logarithmic growth in data and in adoption with big data. Our customers have seen deployments grow from tens of billions of entries to hundreds of billions in a matter of months. That’s another beauty of big data systems: Incremental scalability. Make sure you don’t get lowballed into a BI tool that penalizes your upside.”
The Fifth Commandment remind us all that analyzing the data in its natural, messy form is far better than flattening it into tables due to the risk of losing key relationships. The Ninth and Tenth Commandments step back and look at the big picture of data analytics in 2016. What was only a buzzword to most people just five years ago is now a key aspect of strategy for any number of organizations. This article reminds us that thanks to data visualization, Big Data isn’t just for data scientists anymore. Employees across departments can make use of data to make decisions, but only if they are empowered to do so.
Chelsea Kerwin, April 13, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Delve Is No Jarvis
March 3, 2016
A podcast at SearchContentManagement, “Is Microsoft Delve Iron Man’s Edwin Jarvis? No Way,” examines the ways Delve has yet to live up to its hype. Microsoft extolled the product when it was released as part of the Office 365 suite last year. As any developer can tell you, though, it is far easier to market than deliver polished software. Editor Lauren Horwitz explains:
“While it was designed to be a business intelligence (BI), enterprise search and collaboration tool wrapped into one, it has yet to make good on that vision. Delve was intended to be able to search users’ documents, email messages, meetings and more, then serve up relevant content and messages to them based on their content and activities. At one level, Delve has failed because it hasn’t been as comprehensive a search tool as it was billed. At another level, users have significant concerns about their privacy, given the scope of documents and activities Delve is designed to scour. As BI and SharePoint expert Scott Robinson notes in this podcast, Delve was intended to be much like Edwin Jarvis, butler and human search tool for Iron Man’s Tony Stark. But Delve ain’t no Jarvis, Robinson said.”
So, Delve was intended to learn enough about a user to offer them just what they need when they need it, but the tool did not tap deeply enough into the user’s files to effectively anticipate their needs. On top of that, it’s process is so opaque that most users don’t appreciate what it is doing, Robinson indicated. For more on Delve’s underwhelming debut, check out the ten-minute podcast.
Cynthia Murrell, March 3, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Attivio Does Data Dexterity
October 9, 2015
Enterprise search company Attivio has an interesting post in their Data Dexterity Blog titled “3 Questions for the CEO.” We tend to keep a close eye on industry leader Attivio, and for good reason. In this post, the company’s senior director of product marketing Jane Zupan posed a few questions to her CEO, Stephen Baker, about their role in the enterprise search market. Her first question has Baker explaining his vision for the field’s future, “search-based data discovery”; he states:
“With search-based data discovery, you would simply type a question in your natural language like you do when you perform a search in Google and get an answer. This type of search doesn’t require a visualization tool. So, for example, you could ask a question like ‘tell me what type of weather conditions which exist most of the time when I see a reduction in productivity in my oil wells.’ The answer that comes back, such as ‘snow,’ or ‘sleet,’ gives you insights into how weather patterns affect productivity. Right now, search can’t infer what a question means. They match the words in a query, or keywords, with words in a document. But [research firm] Gartner says that there is an increasing importance for an interface in BI tools that extend BI content creation, analysis and data discovery to non-skilled users. You don’t need to be familiar with the data or be a business analyst or data scientist. You can be anyone and simply ask a question in your words and have the search engine deliver the relevant set of documents.”
Yes, many of us are looking forward to that day. Will Attivio be the first to deliver? The interview goes on to discuss the meaning of the company’s slogan, “the data dexterity company.” Part of the answer involves gaining access to “dark data” buried within organizations’ data silos. Finally, Zupan asks what “sets Attivio apart?” Baker’s answers: the ability to quickly access data from more sources; deriving structure from and analyzing unstructured data; and friendliness to “non-technical” users.
Launched in 2008, Attivio is headquartered in Newton, Massachusetts. Their team includes folks with an advantageous combination of backgrounds: in search, database, and business intelligence companies.
Cynthia Murrell, October 9, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Business Intelligence and Data Science: There Is a Difference
October 6, 2015
An article at the SmartDataCollective, “The Difference Between Business Intelligence and Real Data Science,” aims to help companies avoid a common pitfall. Writer Brigg Patton explains:
“To gain a competitive business advantage, companies have started combining and transforming data, which forms part of the real data science. At the same time, they are also carrying out Business Intelligence (BI) activities, such as creating charts, reports or graphs and using the data. Although there are great differences between the two sets of activities, they are equally important and complement each other well.
“For executing the BI functions and data science activities, most companies have professionally dedicated BI analysts as well as data scientists. However, it is here that companies often confuse the two without realizing that these two roles require different expertise. It is unfair to expect a BI analyst to be able to make accurate forecasts for the business. It could even spell disaster for any business. By studying the major differences between BI and real data science, you can choose the right candidate for the right tasks in your enterprise.”
So fund both, gentle reader. Patton distinguishes each position’s area of focus, the different ways they use and look at data, and their sources, migration needs, and job processes. If need to hire someone to perform these jobs, check out this handy clarification before you write up those job descriptions.
Cynthia Murrell, October 6, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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