Data Analytics
REFERENCES
* ogcio.gov.hk
* Hong Kong Productivity Council
* Mitsubishi UFJ Securities (HK) Holdings Ltd

 



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Feel free to discuss with us your needs on Data Analytics, Hadoop and Spark platform. We are delighted to provide the following services:

# in-house training
# consultancy
# data analytics tailor-made project


What is Data Analytics

Data Analytics is the use of advanced analytic techniques on very large and diverse data sets including structured and unstructured data, streaming (real time data in very large scale) and batch data. Enormous amount of data comes from sensors, devices, video/audio, networks, log files, web, social media and internal applications data. The size and type of data sets are beyond the ability of traditional relational databases to manage and process.

Using advanced analytics techniques such as predictive analytics, machine learning, statistics, data mining, text analytics and natural language processing, business can analyze previously untapped data sources independently or together with their existing internal data. It allows business users, researchers, analysts to make significantly better and faster decisions upon objective data that was previously inaccessible and unusable.

Some of the usages are as follows:

(A) Predictive Analytics

It is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical internal and external data.

Predictive models use known results to train a model that will be used for predicting values for new data. The model generates a probability of the target variable values based on a set of input variables.

What can predictive analytics do

# Identify trends


# Understand customers


# Improve business performance


# Provide direction for strategic planning



(B) Web Log & Click Stream analysis

Click stream is a recording of the parts of the screen a computer user clicks on while web browsing and is logged inside the web server. Web log is server log file from a web server. It provides detailed information on when, how and by whom a web server is visited.

The results of click streams and web log analysis can be used as follows:

# Customer Behavior

# Personalize Marketing

# Improve customer Loyalty



(C) Text Mining / Sentiment Analysis

This includes mining and analyzing text-based information from documents, reports, emails, news feed, database, web-sites, blogs, and social media, e.g. the information in the company's internal documents, and information on Facebook, twitter, Google, Yahoo, LinkedIn, and other websites to derive relevant, new, useful high-quality information and actionable business insights.

Based on the text-based analytics, a company can perform sentiment analysis: analyze the unstructured text of websites contents, blogs, social media, social networking posts, incoming documents and emails to determine the user sentiment related to particular companies, brands or products.







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