CGI

FEBRUARY 7, 2013

Thu, 02/07/2013 - 07:00. Indeed, this seems to be what the C-suite is crying out for, especially in these days of truly disruptive technology megatrends like utility computing, social media and unstructured analytics. CIOs must back technology innovation. ravi.kumarv@cgi.com.

Manufacturing 40

Manufacturing Analytics IT 40

CGI

JULY 16, 2013

Tue, 07/16/2013 - 08:00. How many of you believe that large investments for data analytics are still an issue (20%). Getting Value from New Data Sources In Policing – Part 2, Limited By Search. ravi.kumarv@cgi.com. Again, I asked the audience the following questions. The % figures represent a positive answer.

Unstructured data 40

Unstructured data e-Discovery Analytics Risk 40

CGI

FEBRUARY 20, 2013

Wed, 02/20/2013 - 07:00. We’re happy with our methods for most of the talked-about trends (analytics, social media, mobility, cloud…). So can CIOs afford to ignore AR in 2013? . Consciously Consider Early Adoption. ravi.kumarv@cgi.com. How will you find the right end-user technologies, many of which are still emerging?

Military 40

Military Retail Cloud Analytics 40

Data Matters

SEPTEMBER 29, 2021

In addition, a number of search, analytics, and machine-learning approaches can help identify documents that are likely to implicate privacy concerns. 12-2515, 2013 WL 3974535, at *2 (E.D. 07-2319, 2009 WL 722056, at *7 (D. Production. Haydel Enters., 3d 448, 460 (6th Cir. 2008); see also White v. 3d 448, 460 (6th Cir.

Privacy 97

Privacy e-Discovery Computer and Electronics e-Delivery 97

CGI

NOVEMBER 6, 2013

Thu, 11/07/2013 - 00:18. emails), in the context of the vendor or customer object in an ERP system, or the use of analytics engines against social feeds. Enabling Enterprise Manoeuvrability with EIM. narmada.devarajan. The Agility Challenge. Since the 1990’s, Agile methodologies have gained credibility in project delivery.

B2C 40

B2C Marketing Unstructured data B2B 40

CGI

FEBRUARY 11, 2013

Mon, 02/11/2013 - 07:00. Semantic search, using meaning based computing and natural language analytics. Challenges include: Trawling, aggregating and mining of data, entity extraction to understand what the data actually is, Visualisation and Natural Language analytics, especially multi language. ravi.kumarv@cgi.com.

Mining 40

Mining Big data Analytics Unstructured data 40