Big data analytics: Techniques for large-scale business data
Order ID |
53563633773 |
Type |
Essay |
Writer Level |
Masters |
Style |
APA |
Sources/References |
4 |
Perfect Number of Pages to Order |
5-10 Pages |
Description/Paper Instructions
Big data analytics: Techniques for large-scale business data
The emergence of Big Data has opened up a whole new world of opportunities for businesses to gain insights into their operations and customers. However, dealing with the sheer volume of data generated can be a challenge, and this is where Big Data Analytics comes in. In this blog, we’ll explore some of the techniques that businesses can use to analyze their large-scale data.
- Hadoop
Hadoop is an open-source software framework that provides a way to store and process large amounts of data across clusters of computers. It has become the de facto standard for Big Data Analytics and is widely used by companies such as Facebook, Yahoo, and LinkedIn. Hadoop uses a distributed file system (HDFS) to store data across multiple nodes, and it uses a programming model called MapReduce to process the data in parallel across the nodes.
- NoSQL Databases
NoSQL databases are designed to handle large volumes of unstructured and semi-structured data. Unlike traditional relational databases, NoSQL databases don’t require a fixed schema, which means they can easily handle changes to the data over time. They also offer horizontal scalability, which allows them to handle large amounts of data across multiple nodes. Some popular NoSQL databases include MongoDB, Cassandra, and Couchbase.
- Data Warehousing
Data warehousing is a technique for storing and managing large amounts of data in a centralized repository. It involves extracting data from multiple sources, transforming it into a common format, and loading it into a data warehouse. Data warehouses are optimized for querying and reporting and are typically used for business intelligence and decision-making. Some popular data warehousing solutions include Amazon Redshift, Snowflake, and Google BigQuery.
- Machine Learning
Machine learning is a field of study that involves teaching computers to learn from data without being explicitly programmed. It is particularly useful for analyzing large-scale data because it can identify patterns and trends that might be difficult for humans to spot. Machine learning can be used for a wide range of applications, including predictive analytics, natural language processing, and image recognition.
- Text Analytics
Text analytics is a technique for analyzing large volumes of unstructured text data, such as emails, social media posts, and customer feedback. It involves using natural language processing (NLP) techniques to extract meaning from the text and identify patterns and trends. Text analytics can be used for a wide range of applications, including sentiment analysis, topic modeling, and entity extraction.
- Visualization
Visualization is a technique for representing data visually, often in the form of charts, graphs, and maps. It is particularly useful for analyzing large-scale data because it can help to identify patterns and trends that might be difficult to spot in raw data. Visualization can be used for a wide range of applications, including data exploration, trend analysis, and decision-making.
Big data analytics: Techniques for large-scale business data
RUBRIC
QUALITY OF RESPONSE |
NO RESPONSE |
POOR / UNSATISFACTORY |
SATISFACTORY |
GOOD |
EXCELLENT |
Content (worth a maximum of 50% of the total points) |
Zero points: Student failed to submit the final paper. |
20 points out of 50: The essay illustrates poor understanding of the relevant material by failing to address or incorrectly addressing the relevant content; failing to identify or inaccurately explaining/defining key concepts/ideas; ignoring or incorrectly explaining key points/claims and the reasoning behind them; and/or incorrectly or inappropriately using terminology; and elements of the response are lacking. |
30 points out of 50: The essay illustrates a rudimentary understanding of the relevant material by mentioning but not full explaining the relevant content; identifying some of the key concepts/ideas though failing to fully or accurately explain many of them; using terminology, though sometimes inaccurately or inappropriately; and/or incorporating some key claims/points but failing to explain the reasoning behind them or doing so inaccurately. Elements of the required response may also be lacking. |
40 points out of 50: The essay illustrates solid understanding of the relevant material by correctly addressing most of the relevant content; identifying and explaining most of the key concepts/ideas; using correct terminology; explaining the reasoning behind most of the key points/claims; and/or where necessary or useful, substantiating some points with accurate examples. The answer is complete. |
50 points: The essay illustrates exemplary understanding of the relevant material by thoroughly and correctly addressing the relevant content; identifying and explaining all of the key concepts/ideas; using correct terminology explaining the reasoning behind key points/claims and substantiating, as necessary/useful, points with several accurate and illuminating examples. No aspects of the required answer are missing. |
Use of Sources (worth a maximum of 20% of the total points). |
Zero points: Student failed to include citations and/or references. Or the student failed to submit a final paper. |
5 out 20 points: Sources are seldom cited to support statements and/or format of citations are not recognizable as APA 6th Edition format. There are major errors in the formation of the references and citations. And/or there is a major reliance on highly questionable. The Student fails to provide an adequate synthesis of research collected for the paper. |
10 out 20 points: References to scholarly sources are occasionally given; many statements seem unsubstantiated. Frequent errors in APA 6th Edition format, leaving the reader confused about the source of the information. There are significant errors of the formation in the references and citations. And/or there is a significant use of highly questionable sources. |
15 out 20 points: Credible Scholarly sources are used effectively support claims and are, for the most part, clear and fairly represented. APA 6th Edition is used with only a few minor errors. There are minor errors in reference and/or citations. And/or there is some use of questionable sources. |
20 points: Credible scholarly sources are used to give compelling evidence to support claims and are clearly and fairly represented. APA 6th Edition format is used accurately and consistently. The student uses above the maximum required references in the development of the assignment. |
Grammar (worth maximum of 20% of total points) |
Zero points: Student failed to submit the final paper. |
5 points out of 20: The paper does not communicate ideas/points clearly due to inappropriate use of terminology and vague language; thoughts and sentences are disjointed or incomprehensible; organization lacking; and/or numerous grammatical, spelling/punctuation errors |
10 points out 20: The paper is often unclear and difficult to follow due to some inappropriate terminology and/or vague language; ideas may be fragmented, wandering and/or repetitive; poor organization; and/or some grammatical, spelling, punctuation errors |
15 points out of 20: The paper is mostly clear as a result of appropriate use of terminology and minimal vagueness; no tangents and no repetition; fairly good organization; almost perfect grammar, spelling, punctuation, and word usage. |
20 points: The paper is clear, concise, and a pleasure to read as a result of appropriate and precise use of terminology; total coherence of thoughts and presentation and logical organization; and the essay is error free. |
Structure of the Paper (worth 10% of total points) |
Zero points: Student failed to submit the final paper. |
3 points out of 10: Student needs to develop better formatting skills. The paper omits significant structural elements required for and APA 6th edition paper. Formatting of the paper has major flaws. The paper does not conform to APA 6th edition requirements whatsoever. |
5 points out of 10: Appearance of final paper demonstrates the student’s limited ability to format the paper. There are significant errors in formatting and/or the total omission of major components of an APA 6th edition paper. They can include the omission of the cover page, abstract, and page numbers. Additionally the page has major formatting issues with spacing or paragraph formation. Font size might not conform to size requirements. The student also significantly writes too large or too short of and paper |
7 points out of 10: Research paper presents an above-average use of formatting skills. The paper has slight errors within the paper. This can include small errors or omissions with the cover page, abstract, page number, and headers. There could be also slight formatting issues with the document spacing or the font Additionally the paper might slightly exceed or undershoot the specific number of required written pages for the assignment. |
10 points: Student provides a high-caliber, formatted paper. This includes an APA 6th edition cover page, abstract, page number, headers and is double spaced in 12’ Times Roman Font. Additionally, the paper conforms to the specific number of required written pages and neither goes over or under the specified length of the paper. |
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