GoodReads.com Adds Book Titled Big Data Governance To Its List - Book Titled Big Data Governance Reveals Security Vulnerabilities and Best Practices to Secure Hadoop through Proper Governance
The book offers architectural diagrams and blueprints for successful implementation of data governance for big data lakes using Hadoop instances such as Cloudera, Horton Works and MAPR.
The book includes several chapters that highlight the security and data governance gaps associated with Hadoop and several solution components to develop data governance structure, organization and software platform. These topics include data privacy, data sovereignty, data access controls, data councils, data governance, data quality, meta-data management and data lifecycle management for Hadoop infrastructures such as Cloudera, Horton Works, and MAPR.
“Many IT organizations are finding their data governance policies either inadequate or incomplete when it comes to their massive big data lakes”, said Peter Ghavami, “This book identifies gaps in data governance across enterprise. It’s an excellent handbook for IT security professionals because it offers ready-to-use template and recipes for building a data governance structure including key policies that must be considered for an enterprise wide data governance initiative.”
The book offers a comprehensive look at big data best practices in data governance, data lakes, Hadoop and open source Apache tools. More information about the book can be found at: amazon.com/Big-Data-Governance-Management-Principles-ebook/dp/B01AF0L0KS/.
The book reveals secrets to simple and low cost implementations of data governance across the enterprise. It suggests several architectural drawings for authentication, security, data privacy and access controls including Sentry, Kerberos, Ranger and other Apache tools such as the Atlas project.
“Creating a data governance guideline from scratch is not easy, in particular for big data analytics”, said Peter Ghavami, “IT professionals and security consultants will love this book since it contains a data governance handbook template that can be easily adopted as a starting point for drafting big data governance policies for organizations of any size”, the author added.
The book is written for IT leaders, CIO, CTO, Chief Data Officers, Chief Security Officers, IT security professionals, consultants, data analysts and data scientists who want to learn how to protect their big data assets and bring the entire enterprise data analytics under governance.
“One of the challenges in developing data governance is spotting which policies to adopt and in what hierarchy”, said Peter Ghavami, “Big Data Governance offers specific policy templates for proper data security measures such as file structures, access controls and privacy methods such as tokenization. The book saves IT professionals a lot of time and consulting costs since it includes ready-to-use policies and governance templates for big data”.
The book packs years of consulting experience and best practices by the author, into a readable and easy to read handbook. The book explains challenges with big data security, best practices for securing data and offers tips and best practices for forming organizational structures, the role of data custodians, data stewards and data risk officers.
Peter Ghavami, Ph.D. is a world renowned consultant and best-selling author of several IT books. He has been consultant and advisor to many Fortune 500 companies in the world for IT strategy, big data analytics, innovation and new technology development. His book on application of analytics to clinical data titled Clinical Intelligence is a best-selling book in healthcare (https://www.amazon.com/Clinical-Intelligence-Analytics-Revolution-Healthcare/dp/1500428590/) and a book titled Big Data Analytics Methods (https://www.amazon.com/Big-Data-Analytics-Methods-Techniques/dp/1530414830). His first book titled Lean, Agile and Six Sigma IT Management is still widely used by IT professionals around the world (https://www.amazon.com/Agile-Sigma-Information-Technology-Management/dp/1440478120/). His books have been selected as text books by several universities. Dr. Ghavami has over 25 years of experience in technology development, IT leadership, data analytics, supercomputing, software engineering and innovation. He can be reached at email@example.com.
8226 125th Place, NE, Kirkland. WA 98033
This release was published on openPR.
Permanent link to this press release:
Please set a link in the press area of your homepage to this press release on openPR. openPR disclaims liability for any content contained in this release.
You can edit or delete your press release GoodReads.com Adds Book Titled Big Data Governance To Its List - Book Titled Big Data Governance Reveals Security Vulnerabilities and Best Practices to Secure Hadoop through Proper Governance here
News-ID: 356946 • Views: 510
More Releases for Data
HOW TO TRANSFORM BIG DATA TO SMART DATA USING DATA ENGINEERING?
We are at the cross-roads of a universe that is composed of actors, entities and use-cases; along with the associated data relationships across zillions of business scenarios. Organizations must derive the most out of data, and modern AI platforms can help businesses in this direction. These help ideally turn Big Data into plug-and-play pieces of information that are being widely known as Smart Data. Specialized components backed up by AI and
Global Data Analytics Outsourcing Market |data analytics outsourcing, big data o …
Market Research Reports Search Engine (MRRSE) has been serving as an active source to cater intelligent research report to enlighten both readers and investors. This research study titled “Global Data Analytics Outsourcing Market “ The report on data analytics outsourcing market provides analysis for the period 2016 – 2026, wherein 2018 to 2026 is the forecast period and 2017 is the base year. The report covers major trends and technologies playing
Test Data Management (TDM) Market - test data profiling, test data planning, tes …
The report categorizes the global Test Data Management (TDM) market by top players/brands, region, type, end user, market status, competition landscape, market share, growth rate, future trends, market drivers, opportunities and challenges, sales channels and distributors. This report studies the global market size of Test Data Management (TDM) in key regions like North America, Europe, Asia Pacific, Central & South America and Middle East & Africa, focuses on the consumption
Data Prep Market Report 2018: Segmentation by Platform (Self-Service Data Prep, …
Global Data Prep market research report provides company profile for Alteryx, Inc. (U.S.), Informatica (U.S.), International Business Corporation (U.S.), TIBCO Software, Inc. (U.S.), Microsoft Corporation (U.S.), SAS Institute (U.S.), Datawatch Corporation (U.S.), Tableau Software, Inc. (U.S.) and Others. This market study includes data about consumer perspective, comprehensive analysis, statistics, market share, company performances (Stocks), historical analysis 2012 to 2017, market forecast 2018 to 2025 in terms of volume, revenue, YOY
Long Term Data Retention Solutions Market - The Increasing Demand For Big Data W …
Data retention is a technique to store the database of the organization for the future. An organization may retain data for several different reasons. One of the reasons is to act in accordance with state and federal regulations, i.e. information that may be considered old or irrelevant for internal use may need to be retained to comply with the laws of a particular jurisdiction or industry. Another reason is to
Data Quality and Data Governance Solution Market - Demand For Cost-Effective Dat …
In the enterprise data management ecosystem, data quality is a broad term which refers to the quality, integrity, and consistency of data and/or process etc. Data quality also implies the degree of data accuracy and consistency. On the other hand, data governance focusses on the management of data assets by assigning authority, control, and responsibility of data and encompasses three key areas: people, process, and technology. Data quality and data governance