Data Processing, Systems and Concepts
Author: Robert J. Verzello
Publisher: McGraw-Hill Companies
Published: 1982
Total Pages: 570
ISBN-13: 9780070673250
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Author: Robert J. Verzello
Publisher: McGraw-Hill Companies
Published: 1982
Total Pages: 570
ISBN-13: 9780070673250
DOWNLOAD EBOOKAuthor: Steven L. Mandell
Publisher:
Published: 1985
Total Pages: 746
ISBN-13:
DOWNLOAD EBOOKAuthor: Ralph M. Stair
Publisher: Homewood, Ill. : R.D. Irwin
Published: 1984
Total Pages: 660
ISBN-13:
DOWNLOAD EBOOKAuthor: William H. Desmonde
Publisher: Englewood Cliffs, N.J. : Prentice-Hall
Published: 1964
Total Pages: 210
ISBN-13:
DOWNLOAD EBOOKAuthor: Gary B. Shelly
Publisher: Brooks/Cole
Published: 1980
Total Pages: 516
ISBN-13:
DOWNLOAD EBOOKAuthor:
Publisher:
Published: 1984
Total Pages:
ISBN-13:
DOWNLOAD EBOOKAuthor: Beryl Robichaud
Publisher: Gregg Division McGraw-Hill
Published: 1977
Total Pages: 360
ISBN-13:
DOWNLOAD EBOOKIntroduces the Nontechnical User to Computers & Programming in BASIC. Supplies Information on Computer-Related Career Opportunities
Author: Balamurugan Balusamy
Publisher: John Wiley & Sons
Published: 2021-03-15
Total Pages: 368
ISBN-13: 1119701872
DOWNLOAD EBOOKLearn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.
Author: Susan Wooldridge
Publisher: Elsevier
Published: 2013-10-22
Total Pages: 272
ISBN-13: 1483105245
DOWNLOAD EBOOKData Processing: Made Simple, Second Edition presents discussions of a number of trends and developments in the world of commercial data processing. The book covers the rapid growth of micro- and mini-computers for both home and office use; word processing and the 'automated office'; the advent of distributed data processing; and the continued growth of database-oriented systems. The text also discusses modern digital computers; fundamental computer concepts; information and data processing requirements of commercial organizations; and the historical perspective of the computer industry. The computer hardware and software and the development and implementation of a computer system are considered. The book tackles careers in data processing; the tasks carried out by the data processing department; and the way in which the data processing department fits in with the rest of the organization. The text concludes by examining some of the problems of running a data processing department, and by suggesting some possible solutions. Computer science students will find the book invaluable.
Author: Martin L. Rubin
Publisher:
Published: 1970
Total Pages: 392
ISBN-13:
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