Big Data vs Data Mining
1. Introduction
What is Big Data?
Big Data refers to huge volume of data that can be structured, semi-structured and unstructured. It comprises of 5 Vs i.e.
a. Volume: It refers to amount of data or size of data that can be in quintillion when comes to big data.
b. Variety: It refers to different types of data like social media, web server logs etc.
c. Velocity: It refers to how fast data is growing, data is exponentially growing and at a very fast rate.
d. Veracity: It refers to uncertainty of data like social media means if the data can be trusted or not.
e. Value: It refers to the data which we are storing and processing is worth and how we are getting benefit from this huge amount of data.
Big data can be analyzed
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Mining different types of Knowledge in databases
b. Handling noise and incomplete data
c. Efficiency and scaling of data mining algorithms
d. Handling relational and complex types of data
e. Protection of data security, integrity and privacy
2. Data Mining and Big Data Comparison
Feature Data Mining Big Data
Focus It mainly focusses on lots of details of a data It mainly focusses on lots of relationships between data
View It is a close up view of data It is the Big Picture of data
Data It expresses what about the data It expresses Why of the data
Volume It can be used for small data or big data It refers to large amount of data sets
Definition It is a technique for analyzing data It is a concept than a precise term
Data Types Structured data, relational and dimensional database. Structured, Semi-Structured and Unstructured data (in NoSQL)
Analysis Mainly Statistical Analysis, focus on prediction and discovery of business factors on small scale. Mainly data analysis, focus on prediction and discovery of business factors on large scale.
Results Mainly for strategic decision making Dashboards and predictive measures
3. Key
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Main concept in Data Mining is to dig deep into analyzing the patterns and relationships of data that can be use further in Artificial Intelligence, Predictive Analysis etc. But main concept in Big Data is the source, variety, volume of data and how to store and process this amount of data.
Analyzing of Big data to give a business solution or to make a business definition plays a crucial role to determine
Datatype Description smallint 1 byte is the minimum storage needed int Uses only the bytes that are needed. For example, if a value can be stored in 1 byte, storage will take only 1 byte bigint Uses only the bytes that are needed. For example, if a value can be stored in 1 byte, storage will take only 1 byte decimal This storage is exactly same as the vardecimal storage format datetime Uses the integer data representation by using two 4-byte integers. The integer value represents the number of days with base date of 1/1/1900. The first 2 bytes can represent up to the year 2079.
Sqoop: A project for transferring/importing data between relational databases and Hadoop. Oozie: An orchestration and work flow management for dependent Hadoop jobs. Figure 2 gives an overview of the Big Data analysis tools which are used for efficient and precise data analysis and management jobs. The Big Data Analysis and management setup can be understood through the layered structured defined in the figure. The data storage part is dominated by the HDFS distributed file system architecture and other architectures available are Amazon Web Service, HBase and Cloud Store etc.
Performance Metrics: Metrics should be established to measure the success of the marketing plan
For example, learning collaborative, and sharing of tools and resources. Dashboards is use to measures the bench marks of an ACO’s performances status. A dashboard aids individual ACOs to see their performance results and benchmarks against other competitors. Dashboards can also be used to view the status across the platform.
However, to quantify information means not only involving numbers or
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Therefore, the database can be any type such as SQL, Not Only SQL (NOSQL), or other. Observation_4: The CSP needs to apply a virtualization technology on storage resources to serve CSUs’ demands efficiently. Therefore, a
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Amazon is purely an online sales portal. Based on premium web rating organizations Amazon has a position ranging from 4 to 10 on a global ranking of premium websites. The presence of Amazon in the virtual world of internet is unquestionable. Big Data is a technology area which is highly talked about during the last several years. During the last 18 months, companies in the retail sector, manufacturing, construction, and technology areas have realized the extreme potential of Big Data and are trying to gain maximum advantage from it.
Big Data refers to the massive amounts of structured and unstructured data that is collected over time from various internal as well as external sources. Enterprises are facing challenges in integrating these new and different types of data and also turning this data into meaningful information. The data is growing at a tremendous rate due to increase in connectedness of machines and people. Analyzing this data to extract sensible and meaningful insights is a big challenging task; integrating and optimizing this data, storing, organizing and analyzing is a challenge. The Big Data must be captured, stored, organized and analyzed to influence the decision making in any enterprise or business
Big Data There are many different definitions for Big Data. SAS (n.d.) an analytical software company describes it as, “a popular term used to describe the exponential growth and availability of data, both structured and unstructured.” Many think Big Data just came into existence but it has been around for years. Banks, retail, advertisers have been using big data for marketing purposes.
However, financial performance subsists with different levels of organisation, which is concerned with measuring financial performance of organisation. These measures are categorised into four that includes profitability, gearing, liquidity or working capital, and investor ratios. However, the financial plan of organisation is associated with operating plan since financial plan involves revenue and expenses for the activities that are linked with each objective. Hence, the main reason, in monitoring financial plan is to audit the committee (Hasan, 2011).
Alphanumeric data, Numbers, Characters, Image data, Graphic shapes are the different forms of data. It also includes audio and