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001 9780429343957
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008 210719s2021 nyua ob 001 0 eng d
040 _aOCoLC-P
_beng
_erda
_epn
_cOCoLC-P
020 _a9781000433999
_q(ePub ebook)
020 _a1000433994
_q(ePub ebook)
020 _a9781000433982
_q(PDF ebook)
020 _a1000433986
_q(PDF ebook)
020 _a9780429343957
_q(ebook)
020 _a0429343957
_q(ebook)
020 _z9780367359713
_q(hbk.)
024 7 _a10.4324/9780429343957
_2doi
035 _a(OCoLC)1264403995
035 _a(OCoLC-P)1264403995
050 4 _aQ335
072 7 _aBUS
_x041000
_2bisacsh
072 7 _aBUS
_x071000
_2bisacsh
072 7 _aBUS
_x083000
_2bisacsh
072 7 _aKJC
_2bicssc
082 0 4 _a006.3
_223
100 1 _aBurk, Scott William,
_d1961-
_eauthor.
245 1 0 _aIt's all analytics.
_nPart II,
_pDesigning an integrated AI, analytics, and data science architecture for your organization /
_cScott Burk, David Sweener, Gary Miner.
250 _a1st.
264 1 _aNew York :
_bProductivity Press,
_c2021.
300 _a1 online resource :
_billustrations (black and white)
336 _atext
_2rdacontent
336 _astill image
_2rdacontent
337 _acomputer
_2rdamedia
338 _aonline resource
_2rdacarrier
505 0 _a<P>Part 1: Designing for Organizational Success</P><P>Chapter 1: Some Say it Starts with Data, It Doesn't</P><P>Chapter 2: The Anatomy of a Business Decision</P><P>Chapter 3: Trustworthy AI</P><B><P>Part 2: Designing for Data Success</P></B><P>Chapter 4: Data Design for Success</P><P>Chapter 5: Data in Motion, Data Pipes, APIs, Microservices, Streaming, Events and More</P><P>Chapter 6: Data Stores, Warehouses, Big Data, Lakes and Cloud Data</P><P>Chapter 7: Data Virtualization</P><P>Chapter 8: Data Governance and Data Management</P><P>Chapter 9: Miscellanea -- Curated, Purchased, Nascent and Future Data</P><B><P>Part 3: Designing for Analytics Success</P></B><P>Chapter 10: Technology to Create Analytics</P><P>Chapter 11: Technology to Communicate and Act Upon Analytics</P><P>Chapter 12: To Build, Buy, or Outsource Analytics Platform</P>
520 _aUp to 70% and even more of corporate Analytics Efforts fail!!! Even after these corporations have made very large investments, in time, talent, and money, in developing what they thought were good data and analytics programs. Why? Because the executives and decision makers and the entire analytics team have not considered the most important aspect of making these analytics efforts successful. In this Book II of "It's All Analytics!" series, we describe two primary things: 1) What this "most important aspect" consists of, and 2) How to get this "most important aspect" at the center of the analytics effort and thus make your analytics program successful. This Book II in the series is divided into three main parts: Part I, Organizational Design for Success, discusses . The need for a complete company / organizational Alignment of the entire company and its analytics team for making its analytics successful. This means attention to the culture - the company culture culture!!! To be successful, the CEO's and Decision Makers of a company / organization must be fully cognizant of the cultural focus on establishing a center of excellence in analytics'. Simply, "culture - company culture" is the most important aspect of a successful analytics program. The focus must be on innovation, as this is needed by the analytics team to develop successful algorithms that will lead to greater company efficiency and increased profits. Part II, Data Design for Success, discusses .. Data is the cornerstone of success with analytics. You can have the best analytics algorithms and models available, but if you do not have good data, efforts will at best be mediocre if not a complete failure. This Part II also goes further into data with descriptions of things like Volatile Data Memory Storage and Non-Volatile Data Memory Storage, in addition to things like data structures and data formats, plus considering things like Cluster Computing, Data Swamps, Muddy Data, Data Marts, Enterprise Data Warehouse, Data Reservoirs, and Analytic Sandboxes, and additionally Data Virtualization, Curated Data, Purchased Data, Nascent & Future Data, Supplemental Data, Meaningful Data, GIS (Geographic Information Systems) & Geo Analytics Data, Graph Databases, and Time Series Databases. Part II also considers Data Governance including Data Integrity, Data Security, Data Consistency, Data Confidence, Data Leakage, Data Distribution, and Data Literacy. Part III, Analytics Technology Design for Success, discusses . Analytics Maturity and aspects of this maturity, like Exploratory Data Analysis, Data Preparation, Feature Engineering, Building Models, Model Evaluation, Model Selection, and Model Deployment. Part III also goes into the nuts and bolts of modern predictive analytics, discussing such terms as AI = Artificial Intelligence, Machine Learning, Deep Learning, and the more traditional aspects of analytics that feed into modern analytics like Statistics, Forecasting, Optimization, and Simulation. Part III also goes into how to Communicate and Act upon Analytics, which includes building a successful Analytics Culture within your company / organization. All-in-all, if your company or organization needs to be successful using analytics, this book will give you the basics of what you need to know to make it happen.
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aArtificial intelligence.
650 0 _aDecision making.
650 0 _aVisual analytics.
650 0 _aBig data.
650 7 _aBUSINESS & ECONOMICS / Management
_2bisacsh
650 7 _aBUSINESS & ECONOMICS / Leadership
_2bisacsh
650 7 _aBUSINESS & ECONOMICS / Information Management
_2bisacsh
700 1 _aSweenor, David,
_eauthor.
700 1 _aMiner, Gary,
_eauthor.
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9780429343957
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999 _c5538
_d5538