From the book "Data Strategy: : How to Profit from a World of Big Data, Analytics and the Internet of Things"
Read Introduction and Chapter 1 and do the following:
1. Executive Summary for EACH chapter.
2. Which are the three most CRITICAL ISSUES of EACH chapter? Please explain why? and analyze, and discuss in great detail …
3. Which are the three most relevant LESSONS LEARNED of EACH chapter? Please explain why? and analyze, and discuss in great detail …
4. Which are the three most important BEST PRACTICES of EACH chapter? Please explain why? and analyze, and discuss in great detail …
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Business intelligence can be defined as an activity in which the raw data is converted into meaningful and ore applicable information for the business for some kind of analysis applications. The main things which are analyzed in this are the process optimization and radical changes in any activity or process. The reports are made with the help of raw data and dashboard oriented pre-defined metrics which are termed as KPI. In order to fulfill the compliance requirements, the reports obtained from Business intelligence are used. The main feature of BI is that it can is some of the important data which is present in the raw data as it mainly focuses on the aggregation of the data.
On the other hand, the main activity in case of Business Analytics is to derive some sort of relationship on the basis of the historical data with the help of business models and try to forecast the future results. It indicates that the reports of BI are used in it and conventional statistics and moderns tools are used to find out the patterns and relationships.
In business activities, both of these concepts play a very important role. The companies are now trying to use both the concepts in order to find out some variation in the patterns and how one factor changes the outcome of others. On the basis of this, different business-related activities are performed.
The creation and consumption of data continues to rapidly grow around the globe with large investment in big data analytics hardware, software, and services. The availability of large data sets is one of the core reasons that Deep Learning, a sub-set of artificial intelligence (AI), has recently emerged as the hottest tech trend. Huge giants such Google, Facebook, Baidu, Amazon, IBM, Intel, and Microsoft are heavily investing in big data, with the acquisition of talent hot on their agenda.
Big data is continuously creating new challenges and opportunities, all of which have been forged by the information revolution. Using Big Data Analytics, you can uncover various critical pieces of information such as market trends, customer preferences and so on .
e-commerce business can benefit the most from using Big Data,
because of all the information they collect during day-to-day
operations.
Many big retailers know the value of this information and offer
customers many preferences when shopping on their site. These
preferences are all generated from Big Data analytics. There really
is no limit to customer preferences when using this tool. Building
a better customer experience is one of the most
important uses for Big Data. The customer has come to expect
superior treatment from e-commerce business and this data can be
utilised to keep them satisfied. Predictive analytics is used by
e-commerce to predict what the consumer will buy.
Amazon uses this better than anyone with science and not just
relying on their marketing ability.Personalisation involves using
Big Data to personalise emails and
increase conversion rates.
Pricing can be changed constantly to keep up with
competition using real-time analytics.
the problems or challenges with big data are that Big data is any set of data that is so large that the organization that owns it faces challenges related to storing or processing it. In reality, trends like ecommerce, mobility, social media and the Internet of Things (IoT) are generating so much information, that nearly every organization probably meets this criterion.
If your data resides in many different formats, it has the variety associated with big data. For example, big data stores typically include email messages, word processing documents, images, video and presentations, as well as data that resides in structured relational database management systems (RDBMSes).
But i think Big data helps not only e-commerce but other business to gain competitive advantage in the form of upper hand in business like launching new product or services, introducing new pricing strategy for product to deal with competition or meeting customer's demand before competition.
From the book "Data Strategy: : How to Profit from a World of Big Data, Analytics...
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