Business strategy used in the processing chipsets
Table of contents
Enabling Chipset storage and networking using big data 5
Imparting Iot in Microprocessor using big data 5
3.2.4Analysis Tools Used in Big Data Technologies 6
3.3 Big data architecture solution 8
Practical and Written Assessment
1.0 Executive summary
2.0 Introduction
In this recent technological world, data is being generated in various sources for varied purposes which results in the growth of big data. It becomes an evolutionary breakthrough, which aids in the collection of large sets of data. Big data is termed as massive amounts of complex data which is either structured or unstructured and are stored in databases. The objective of big data is to analyze and process high volume of data which uses wide range of technologies and intelligent techniques. Big data comprises of four dimensions as volume, velocity, variety and veracity (Taylor-Sakyi, 2016). It does provide lot of opportunities in knowledge processing tasks which will enable the researches done in this field of study. The bigger challenge prevailing in big data is its storage and accessing of data for the analysis of data. The analysis requires highly computational tools which handle the complexities, uncertainty and inconsistencies existing in the big data in effective manner. Big data is used in various domains like retail industry, scientific researches, healthcare, public administration etc. Big data comprises of various strategies which is used in the analysis of data which is associated with the particular domain. The analysis requires tools and models for further processing of the big data. In this report we will discuss about the big data analysis with respect to the technological advancements prevailing in the field. Further we will have a brief about big data use cases which is related to the assessment done for the Intel micro processing chipsets. Finally, we will have a discussion about the big data techniques and tools or models of big data architecture which is used for processing the solution.
Body of the Report
3.1 Big data use cases
In this section we will have a brief about the use cases of big data in various fields. With respect to the digitalization in the world, big data is used in fields like Chip set designing using big data, storage process, In IoT microprocessor Technologies etc. Here we will have a brief discussion on how the big data is applied in to those fields and its outcomes after applying the big data.
Business Strategy used in the Processing Chipsets
Chipset Designing Based on Big Data
Enabling Chipset Storage and Networking using Big Data
Imparting IoT in Microprocessor using Big Data
3.2 Critical analysis of big data technologies
In this section we will discuss about the analysis techniques of big data. The type of analysis will vary among the different type of industries and sectors. The big data strategy used in the Intel processing chipset is package level integration which aims in obtaining high quality outputs and enhance the innovation in the chipsets processing. The analysis of big data is based on the specific technological needs and requirements. The Technologies used in this process are, Apache Hadoop, Microsoft HDInsight, No SQL, Polybase, Cloud technology.
3.2.1 Hadoop Technology
With the help of Hadoop technology many applications will be run based on MapReduce Algorithm, and here the data is processed in parallel process. Hadoop is a tool which is used to perform the statistical analysis of the large amount of data. It is an Opensource network that is written in Java. It is used for storage and computation process.
3.2.2. Cloud Technology
Descriptive Analysis Tool
Cognitive Analysis Tool
3.2.4Analysis Tools Used in Big Data Technologies
Diagnostic analysis – the diagnostic analysis is used for finding out the root of any issues or problems prevailing in the big data technologies. By means of this analysis, it is determined to know why the problem has occurred. It does help in identifying the causes of the events and the behaviors of the patterns associated with the big data. In the Intel processing chipsets, the diagnosis is made to identify the defects when the system is subjected to big data analysis and its processing. The issues and problems are identified and then the solutions are made to rectify those issues. Here in which the actions are taken according to the report given as it answers the question why it has happened.
Preemptive analysis – this deal with the steps or strategies for precautionary actions or events which necessitate the technologies to prevent from any other issues. It is a sort of precautionary method for the data sources (Uthayasankar Sivarajah, 2016).
3.3 Big data architecture solution
The architecture forms the basis any system. The big data analytical tools have certain framework for its systematic analysis of the data. The complex nature of big data necessitates the requirement of proper architectural system. Here in which we will elaborately study about the Hadoop architecture which is used widely in many enterprises. It is mostly used for the advantage of refined data management even though it processes large amounts of data at low cost (P.Joseph Charles, 2018).
Hadoop framework
Hadoop is a type of open source project which is coming under Apache (M. Sowmya, 2017). As the data analysis includes distributed data processing methods, and programming and the data pre -processing components. The open source project or tools for data management comprises of following categories like, cluster management, data store, distributed file system, governance and security and data ingestion. Both the tools and application are used for the processing of the big data processes. Hadoop is used in many organizations which deals with the storage large volumes of data. Hadoop enhances the scalability and availability of the big data analytics. It does run on multiple cluster system which uses simple programming modules. It is an enhanced methodology which replaces the traditional database management system. This framework will be useful in handling massive volume of data from the storage without any inconsistencies. It is widely accepted in many organizations for big data analysis. There are some additional packages which are also installed with the Hadoop and those packages are called Hadoop ecosystem. It provides effective and efficient solution for the processing and the storage of the data
Another aspect of the architectural framework is the visualization of the data either in pictorial representation or graphical representation which would help in decision making for the complex concepts to identify the patterns of the data source.
4.0 Conclusion
Thus, we conclude that the report is made for the big data analytics in various technologies are made. This paper defined the strategies and techniques prevailed in big data which is helpful in the analysis of the data. The big data storages are comprising of complex data structures which require high computation methods for its analysis. The big data is useful in various fields in the new era of technological development. The organizations which are comprised of large volumes of data are supposed to use big data analytics which makes their system to run without any uncertainties. The big data uses various analysis methods to analyze the data to find out the predictions or patterns associated with the data stored in the database. The analysis gives solution for the future references which will enhance the technological advancement in the big data development. Then the architecture of the analysis of big data is must to perform any analysis in a sequential order. The data may be processed with the order of preference given in the architectural framework and the output is obtained. The tools and techniques of the big data analysis are easy to use and it adheres with the organizational procedures and policies. The tolls used must be varied to the size of the big data prevailing in the organization.
References
Optimizing Manufacturing with the Internet of Things. (n.d.). https://www.intel.in/content/www/in/en/internet-of-things/white-papers/industrial-optimizing-manufacturing-with-iot-paper.html .
P.Joseph Charles, S. T. (2018). BIG DATA – CONCEPTS, ANALYTICS, ARCHITECTURES – OVERVIEW. https://www.irjet.net/archives/V5/i2/IRJET-V5I231.pdf .