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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4 Ways Big Data Analytics Transform Intelligence Data into Actionable Insights

Intelligence and law enforcement agencies experience an enormous pressure to identify threats across multiple data sources. These Defense and Security organizations require real-time information at their fingertips for quick analysis and decision making.

Big Data Search and Analytics for Defense and Security

Big Data Search and Analytics for Defense and Security

Here are 4 ways Big Data Analytics can transform intelligence data into actionable insights:

  • Monitoring of Social Media interactions

Intelligence agencies must anticipate any kind of cybercrime and attacks. Social media monitoring enables them to collect and analyze relevant and targeted information relating to counter-terrorism and criminal networks. Reacting at the right time is a major challenge for these organizations that use OSINT (Open-Source Intelligence) to find, select and acquire information from various sources online (social networks, forums, blogs, websites, videos etc.) in order to get real-time insight on potential threats, generate reports and prevent any kind of attacks. In response to this challenge, intelligence agencies must invest in a cutting-edge technology that brings together data search and collection across multiple online sources and a deep content analytics of unstructured textual data that are flooding the web.

  • Detection of money laundering, fraud & terrorist financing

Money laundering is a key component of most organized crime. Terrorist networks continue to be funded through money laundering schemes that need to be identified. A powerful Big Data Search and Analytics platform enables agents to pinpoint suspect money transfers, accounts and networks of individuals involved in sophisticated money laundering schemes through a highly dynamic approach to relationship mapping.

  • Identify and correlate threats & cyberattacks

Investigators face the daunting task to accurately identify fraud and cyberattacks across big data volumes within shrinking windows of time. To prevent threats and cyberattacks before they happen, intelligence agencies must be able to deliver dynamic relationship mapping to connect people, bank accounts, credit card numbers, financial transactions, and many other data types. They need a scalable platform based on advanced Search and Natural Language Processing capabilities. Analysts uncover patterns in behavior using a combination of interactive charts, timeline analyses, tables and relationship maps.

  • Solve crime cases with powerful search capabilities

Law enforcement professionals need effective crime analysis tools to easily reveal networks of criminal activity. The sophistication of criminal behavior has increased across virtually all areas, including cybercrime, identity theft, gang activity, fraud and narcotics. These tools must provide the ability to search and analyze a wide range of sources of both structured and unstructured data to gain meaningful insights using connections between people, phone calls, license plates, addresses, properties or other forms of data.

To learn more – please download the brochure “Sinequa for Defense and Security”.

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Sinequa and SYSTRAN Join Forces to Exhibit at Milipol, the 19th Worldwide Exhibition of Internal State Security

Combined Solutions Empower Defense and Security Organizations to Transform Intelligence Data into Insight

PARIS, France – November 10, 2015 Sinequa, a leader in real-time Big Data search and analytics and SYSTRAN, the world leader in language translation software, today announced that they will join forces to exhibit at Milipol to be held at Paris-Nord Villepinte – November 17-20th, 2015. In the context of their partnership, Sinequa and SYSTRAN provide state of the art technologies enabling leading defense and security organizations to transform COMINT/OSINT data into insight.

Today’s intelligence and law enforcement agencies around the world are facing ever-growing threats from civil conflicts, weapons of mass destruction, nuclear and chemical arms, money laundering to terrorist acts and cyberattacks. Intelligence analysts need an intuitive way to extract insight from massive-scale data contained in various internal and external sources – this includes everything from signals and transcripts to fund transfers, e-mails and social media. The combination of Sinequa Big Data search and analytics platform along SYSTRAN’s instant translation solutions for more than 45 languages empower defense and security organizations to get real-time information at their fingertips for quick analysis and decision.

“Over the years, Sinequa Big Data Search and Analytics has been deployed by leading defense and intelligence agencies facing huge challenges in terms of data collection, indexing and text analytics,” said Xavier Pornain, VP Sales & Alliances, Sinequa. “In combination, SYSTRAN’s automated translation solutions and Sinequa Big Data Search and Analytics provide these organizations with powerful and innovative technology to detect and process critical information in multiple languages while providing an exhaustive view of a given topic.”

“Sinequa offers strong analytics for structured and textual data in a number of languages. With SYSTRAN, our joint customers can extend the analysis of textual data to more than 45 languages,” said Gilles Montier, Sales Director, SYSTRAN.

Sinequa and SYSTRAN will be exhibiting in the Transmission, Communication and Interception Hall respectively in booths #5F248 and #5G247.

To learn more about Sinequa Defense and Security, please visit: www.sinequa.com/sinequa-defense-security

To learn more about SYSTRAN Defense and Security, please visit: www.systransoft.com

 

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6 Ways Pharma Companies Efficiently Leverage Search-Based Applications (SBA)

Sinequa for Life Sciences

Leading pharma companies are facing big challenges every day. In an ever-more competitive industry, it becomes crucial for these organizations to achieve the following objectives:

  • Speed up submission of New Drug Applications to reduce costs for new drugs development
  • Make educated decisions to continue or stop drug trials based on all clinical trial data available
  • Provide researchers with a unified access across the entire organization to all structured and unstructured data from both internal and external wide variety of sources
  • Drive innovation, accelerate research and shorten Drug Time-to-Market
  • Foster cooperation in R&D while respecting information governance and security
  • Optimize clinical trials and catalyze drug repositioning

Below, we will highlight 6 ways a pharma company can use real-time Big Data Search and Analytics to leverage Search Based Applications (SBA) and raise its competitiveness:

1. Quickly Establish a Network of Experts

You can find a network of experts, e.g. for a drug repositioning project, you will be looking for experts on the related drug, molecules and their Mechanism of Action, medical experts, geneticists, biochemists, etc. For example, you can get an “Expert Graph” calculated from the “footprint” experts leave in texts and data. You can also “link” people by their joint appearance in a document, even to the point of requiring that they be mentioned in the same sentence.

2. Find Scientific Partners/CROs

Similar to the network of experts within your own company, you can extend your search for experts on R&D topics to external research organizations in order to identify the most promising collaboration partners in a given field.

3. R&D Intelligence

Another important point is to discover knowledge in a particular field and detect correlations by sentence-level co-occurrence of topics across all your documents.

4. R&D News Alerts

The access to the latest scientific information of your field with automatic alerts may be of great interest. Via this information, you can discover research trends in your field. This Search Based Application must cover millions of documents: all accessible external data sources, e.g. publications, Embase, Medline, Scopus, clinical trial reports, etc. Internal sources, e.g. SharePoint, Documentum, etc.

5. R&D Search by Chemical Structures

Another way to leverage your SBAs is being able to simply “throw” a drawing of a molecular structure in the search platform, by a drag-and-drop of a .mol description file and automatically detect the drugs using this molecule, their scientific and brand names, the diseases treated with these drugs, etc.

6. Optimize Clinical Trials

You can transform your growing clinical trials data to a valuable asset by building an app that lets you search content with very precise criteria and retrieve subjects that have shown certain diseases by specifying exact or fuzzy values on the right variable for instance. You can also search datasets based on the structure and metadata and search across many drugs and studies, merging current data silos.

Curious to get some concrete use cases at leading pharma companies among our customers? Please download our Life Sciences whitepaper or contact our team for more details!

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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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