solutions and understanding text analytics

1. R. Pavithra,
II-MSc(IT),
Nadar saraswathi college of arts and science,
Theni.

2.  Big data analytics is the process of collecting large chunks of
structured/ unstructured data, segregating and analyzing it and
discovering the patterns and other useful business insights
from it.
 It helps in determining which data is relevant and can be
analyzed to drive better business decision in the future.

3.  Big data has become a key differentiator in helping
organizations forecast and make strategic decisions to remain
competitive and increase revenue, reduce risk and attain
growth .

4. TRAVEL:
-The travel industry generates a vast quantity of data around
reservation, inquiries, itineraries, hotels, rental car, trains,
airlines, fare charts, customer feedback etc.,
-Thus leaving long trails of data.
HEALTHCARE:
- Big data is helping every industry to become more efficient
and productive.
-medicine and health care sector are also not different.

5.  ECOMMERCE &RETAIL :
◦ E-commerce and retailers are prioritizing data collection
from omnichannel and are implementing analytics to
gather relevant business insights which help them reach
more customers and boost sales.
◦ big data analytics play a key role in almost all stages of the
ecommerce and retail selling/buying process.
MANUFACTURING
-manufacturing industry deals with huge amounts
of data from a network of thousands of motors ,heavy duty
mechanical equipment electronic relays and sensors
synchronized& controlled by complex systems.

7.  Text analytics is the process unstructured text data into
meaningful data for analysis , to measure customer opinions ,
product reviews, feedback, to provide search facility,
sentimental analysis and entity modeling to support fact
based decision making.
 It also involves lexical analysis, categorization, clustering,
pattern recognition, tagging, annotation, information
extraction, link and association analysis, visualization, and
predictive analytics.

8.  Provide tools, servers, analytic algorithm based application,
data mining and extraction tools for converting unstructured
data in to meaning data for analysis.

10.  Text mining ,text parsing, text identification, text extraction,
text categorization, text clustering .
 Extraction of concepts , entities, relations events.
 Creation of taxonomies.
 Search access, web crawling, indexing , duplicate document
identification.
 Analyze all major file formats and all major languages- natural
language/ semantic toolkits.

11.  Entity relation modeling.
 Link analysis, link text repositories.
 Ability to identify and analyze sentiments people ,place and
other information from websites , internal files ,reports
surveys , forms, employee surveys, claims, underwriting
notes , medical records, emails, news, blogs, social media,
customer surveys, market surveys, online forums, online
reviews, review sites, scientific journals, web site feed back,
call center logs, transcripts , snail mail, sales notes.
 Documents summarization features and records management.
 Interactive visualization.

12.  Sentiment analysis.
 Search access of unstructured data.
 Automated ad placement.
 Social media monitoring.
 Competitive intelligence
 Scientific discovery, especially life sciences.