Big
data is more extensive, more complex data sets, especially from new data sources. These
data sets are so voluminous that traditional data processing software just
can't manage them. But these massive volumes of data can be used to address
business problems you wouldn't have been able to tackle before. (Oracle.com, 2014)
Types of Big Data
Big
data is more extensive, more complex data sets, especially from new data sources. These
data sets are so voluminous that traditional data processing software just
can't manage them. But these massive volumes of data can be used to address
business problems you wouldn't have been able to tackle before. (Oracle.com, 2014)
Types of Big Data
1. Structured Data
Any
data that can be stored, accessed, and processed in a fixed format is called
structured data.
2. Unstructured Data
Any data with a form or structure unknown is labelled as unstructured data. A typical example of unstructured data is a heterogeneous source of data that contains a combination of simple text files, images, videos, etc.
Any data with a form or structure unknown is labelled as unstructured data. A typical example of unstructured data is a heterogeneous source of data that contains a combination of simple text files, images, videos, etc.
3. Semi-Structured data
Semi-structured data may
contain data in both types. We can see semi-structured data as structured in
form, but it is not defined explicitly in relational DBMS with, e.g., a table
description. Semi-structured data, for example, is a data described in an XML
format.
Advantages and Disadvantages of Big Data
Generally speaking, getting more data on one's clients (and potential customers) will help companies to help refine their offerings and marketing efforts to create the highest level of loyalty and company repeats. Organizations capable of collecting massive amounts of data are allowed to perform more in-depth and more vibrant research. (Guru99.com, 2020)
While a positive thing is better analysis, big data can also generate complexity and noise. Companies must be able to handle larger volumes of data while determining which data represents signals as compared to sound. A key factor will be deciding what makes the data import. (Guru99.com, 2020)
Big Data Tools
Based on popularity and
usability following is the lists of open-source tools: -
2. Apache Spark
3. Apache Storm
4. Cassandra
5. RapidMiner
6. Mongo DB
8. Neo4j
9. Apache
Samoa (Guru99.com, 2020)
References
- Oracle.com. (2014). What Is Big Data? | Oracle Ireland. [online]Available at: https://www.oracle.com/ie/big-data/guide/what-is-big-data.html [Accessed 22 Jan. 2020].
- Guru99.com. (2020). Introduction to BIG DATA: What is, Types, Characteristics & Example. [online]Available at: https://www.guru99.com/what-is-big-data.html [Accessed 22 Jan. 2020].
- Amit Verma (2018). Top 10 Open Source Big Data Tools in 2020 [Updated] - Whizlabs Blog. Whizlabs Blog. Available at: https://www.whizlabs.com/blog/big-data-tools/ [Accessed 23 Jan. 2020].
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