Join Sinequa at Bio-IT World Conference & Expo 2016 (Booth #421)

Sinequa will present and exhibit at Bio IT World Conference & Expo that will take place on April 5-7 at the Seaport World Trade Center in Boston, USA.

Sinequa For Life Sciences

We invite you to stop by the Sinequa booth #421 to discuss innovative use cases of our solution for the Pharma industry – Sinequa For Life Sciences - and see how our customers raised their competitiveness by implementing our Big Data Search and Analytics solution across the most diverse data silos.

  

Also, make sure to book your agenda and attend our presentation in the Bioinformatics Track #5:

Wednesday, April 6, at 2:55-3:10 PM

“Increasing the Competitiveness of Pharma Companies:
Real Time Search and Analytics Across Structured & Unstructured Data”

Speaker: Xavier Pornain, Vice President of WW Sales & Alliances

Book your agenda

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Digital Workplace: Digitized Chaos or Information at your Fingertips?

Digital Workplace

You have a digital Workplace, of course. Does it fulfil all the expectations you had when you went “all digital”? Or is getting at the right information still too complex, too cumbersome and time-consuming? Companies often need specialists to extract information for each specific work context. That is not agileand it’s in total contradiction with the modern digital workplace principles promising “information self-services”.

In decent Digital Workplaces, you find information, not data! And this information must be comprehensive and relevant, and delivered instantly, since in the era of digital business models, there is no time to sift through tons of data when you need information. At best, information is delivered proactively, in order to gain time, increase productivity and improve decision making.

Now, many of you may be wondering: “how to create value from data in increasingly digitalized businesses?”; “how to extract relevant information from big and diverse data and then, deliver precise and relevant information to each and every person at the right time?” This might seem like an elusive goal as we create more data than ever in digitalized workplaces, potentially increasing chaos every day.

To overcome these challenges, we need to simplify the digital workplace for users. This requires high performance systems of data retrieval, analytics and information delivery.

In the past, organizations have installed data warehouses and search engines to help people find relevant data. Many of these never delivered on the expectations – and the needs – of users and organizations. They were lacking in analytical power and in performance when faced with large and growing amounts of heterogeneous data and with the need to combine analysis of structured and unstructured data, including most prominently natural language processing (NLP) for a while range of languages.

The new generation of enterprise search platforms have evolved into whatGartner calls “Insight Engines”.

According to this leading analyst firm, 25% of large organizations will have an explicit strategy to make their corporate computing environment similar to a consumer computing experience by 2018; 46% have a digital workplace initiative underway and 4% have appointed a Digital Workplace leader.

As usual, the bright new digital future cannot be “bought” with a new piece of technology. It requires a change of mind-set and a change in corporate culture.  Nevertheless, be aware that the digital workplace technology you select can either facilitate or impede adoption and change of culture.

Gartner specifies these Digital Workplace Principles : Contribution/ Enthusiasm; Digital Dexterity; Autonomy

#1 Contribution/ Enthusiasm: By promoting employee engagement, digital workplaces create a workforce that makes discretionary contributions to business effectiveness

#2 Digital Dexterity: Creating a “consumer-like computing experience” to enable teams to be more effective

#3 Autonomy:  Exploiting emerging smart technologies and people-centric design to support dynamic non-routine work

To step into the era of the reimagined Digital workplace you need the “Insight Engine” to increase your employees’ effectiveness and productivity, to help them better serve their customers while enjoying their work environment.

Sinequa has been mentioned next to Apple, IBM and the likes in the latest Gartner’s Hype Cycle Content Management/Digital Workplace 2015 Reports – for proactive search capabilities that are mandatory for a transition to Digital Workplaces.

Take a look at our presentation in the Gartner Digital Workplace Summit last September in London:

 “The Re-Imagined Digital Workplace: Where is the Beef?

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3 Key Drivers for a Performant Enterprise Big Data Search and Analytics Platform

If you are aiming at deploying a performant Enterprise Search platform you would do well to consider these 3 key criteria:

Strong Content Analytics

In order to be extremely effective and efficient, an Enterprise Big Data Search and Analytics platform should offer strong Content Analytics that combines indexing of both structured and unstructured data. Indeed, it’s the combination of both types of analysis that delivers more relevant results and insights to users.

In addition, a performant Enterprise Big Data Search and Analytics platform should also “put powerful NLP to work in surprising scenarios” according to Forrester Research. The semantic analysis (named entities extraction, text mining agents, etc.) coupled with the statistical analysis and machine learning algorithms enables data-driven businesses getting more relevant and contextual information from search results.


Big Data Search and Analytics  PlatformHigh Connectivity

A Big Data Search & Analytics platform only deserves its name if it connects easily to virtually all data sources of an organization. If you need access to a new data source, you want to have it now, not in 3 months.

Multiple connectors to structured and unstructured data sources (internal and external to an enterprise) will help you cope with “data variety” and ensure that projects can start delivering value to users in a matter of weeks rather than months.

Extreme Scalability

Your platform architecture should offer the necessary scalability to deal with your large and diverse amounts of Big Data. It should be scalable enough to combine statistical analysis of structured and unstructured data with linguistic and semantic analysis of texts in several major languages (NLP – Natural Language processing). Moreover, an out-of-the box Grid Architecture that allows you to flexibly adapt resources will help you gain agility and get faster response times.

So, is your Enterprise Big Data Search & Analytics platform as performant as you thought?

If not, request a demo here and see how you can get value from your big data easily and rapidly!

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Frankfurt, London, New York… The Sinequa Team Grows Global

90% of all data in the world has been collected in the past 2 years and this is not ready to stop. Large enterprises are challenged by these continuously growing mountains of data, and business leaders must unlock its value to make sense of it all. Thanks to its disruptive technology and its international experts’ teams, Sinequa is helping large organizations to meet this challenge.

The strong traction experienced in 2014 has lead Sinequa to increase its workforce by 25 %, and expand into the United States (NYC).

As part of this growth, we are pleased to announce the appointment of Fabrice de Salaberry as Sinequa’s Chief Operating Officer. Fabrice is a seasoned Executive, used to lead high-tech companies on the road to success.  His successful experience in the fast growing Data Management space as COO of Atempo and then CEO of Active Circle will be precious to drive the expansion of Sinequa within the Big Data Search & Analytics worldwide market.

Our expanded sales team includes:

  • Edward Aballa, Sales Director based in New-York, covering the United States;
  • Graham Wolley, Sales Director based in London, covering the United Kingdom and Ireland;
  • Matthias Hintenaus, Sales Director based in Frankfurt, covering Germany, Austria and Switzerland.

Since inception, Sinequa has formed impressive partnerships with those on the cutting-edge of big data, including AstraZeneca, Biogen Idec and Siemens. With our expanded geographic coverage, our teams aim at helping large organizations in extracting business value from their data. They will contribute in creating innovative applications that revolutionize the way enterprises interact with their large volumes of structured and unstructured data, whether they come from internal or external sources.

Interested in these topics? Reach out to us at: info@sinequa.com

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Finding the Right Expert: Business Critical and Obtainable Through Big Data Analytics

As we recently shared in the Big Data Paris guide, some of the most interesting work in the big data industry happens when large, multi-national organizations look inward and across their business ecosystem, to see what they know and who knows what.

Many organizations are challenged by the need to rapidly, accurately find experts on any given topic within their ranks. They wonder:

  • Who’s keeping track of this information? Where is it stored?
  • How can we find the real experts on a particular technology or an active molecule in a drug when our expertise is spread across continents?
  • What if the expertise is spread through a myriad of affiliated partners, or in the heads of a few people within thousands of personnel?

This is where big data analytics comes into play.

Locating true experts within an organization requires going beyond HR paperwork, Linked-In profiles and CV declarations – right to the work. It’s true: the proof is in the pudding and organizations must sift through publications, project reports, patent filings, HR data and mountains of structured data to find true experts to quickly respond to RFPs, initiate new projects and avoid costly clinical trial repetition. But what about all of that unstructured data? What about when a chemical compound appears in papers via generic name, brand name, scientific name or even a molecular description? Who can tie it all together?

Increasingly, more large enterprise have seen the light and now successfully use data analysis to rapidly, accurately find true experts for better business outcomes. Enormous companies are learning to be more nimble, with the help of big data.

Global biopharmaceutical giant, AstraZeneca, leading industrial company Siemens, and multi-national IT services powerhouse Atos are such companies. These organizations partnered with Sinequa on expert localization, using their greatest asset: data in multiple forms, stored inside and outside of the company. Moving to a partner like Sinequa was a simple decision: the Paris-based company has a unique ability to cull through both structured data and unstructured data – emails, social networks, publications, and reports – to create a richer, fuller picture of the true company experts on any given topic.

To get the complete picture, data must be analyzed using Natural Language Processing (NLP) capacities to “understand” what topics are being written about in real terms. For instance the platform allows for identification of a topic, even beyond words used in queries. Thus, asking for “Aspirin” will deliver results for Acetylsalicylica Acid, 2-Acetoxybenzoic acid, Ecotrin, Acenterine, Acylpyrin, Polopiryna, Easprin, and Acetylsalicylate. The platform can suggest authors, emails and other resources to contact for clarification. It is truly astounding. Even more, a network can be created, linking expert to expert.

Like AstraZeneca and Siemens, Atos has thousands of personnel. Atos had rapid growth in a short time frame, from a French company with 2,000 employees to a global player of more than 80,000 employees across many locations and through partners and alliances. They found a way to solve the problem of quickly finding experts in the organization with a platform that allowed rapid-fire sifting through masses of text and data: identifying authors and concepts to quickly map networks of experts and pinpoint links between them .

Why should all of this matter? Shouldn’t big data be all about capturing customer trends and finding better ways to market externally? Not necessarily.

For companies that take on massive R&D projects or global technology management, for example, finding the right people at the right time can result in significant gains for the enterprise at a time when business success is crucial. It can prevent reinventing solutions already in place, thus freeing financial and human resources for growth. Putting the right people in place on any project can increase customer satisfaction by rapid and competent project implementations, and protect margins.

Teamwork, complementary expertise is most often the underpinnings of innovation and problem solving. People are indeed, the heart of any organization and putting them together accomplishes great things.

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