{"product_id":"blockchain-data-analytics-for-dummies-isbn-9781119651772","title":"Blockchain Data Analytics For Dummies","description":"\u003cp\u003e\u003cb\u003eGet ahead of the curve—learn about big data on the blockchain\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBlockchain came to prominence as the disruptive technology that made cryptocurrencies work. Now, data pros are using blockchain technology for faster real-time analysis, better data security, and more accurate predictions. \u003ci\u003eBlockchain Data Analytics For Dummies \u003c\/i\u003eis your quick-start guide to harnessing the potential of blockchain.\u003c\/p\u003e \u003cp\u003eInside this book, technologists, executives, and data managers will find information and inspiration to adopt blockchain as a big data tool. Blockchain expert Michael G. Solomon shares his insight on what the blockchain is and how this new tech is poised to disrupt data. Set your organization on the cutting edge of analytics, before your competitors get there!\u003c\/p\u003e \u003cul\u003e \u003cli\u003eLearn how blockchain technologies work and how they can integrate with big data\u003c\/li\u003e \u003cli\u003eDiscover the power and potential of blockchain analytics\u003c\/li\u003e \u003cli\u003eEstablish data models and quickly mine for insights and results\u003c\/li\u003e \u003cli\u003eCreate data visualizations from blockchain analysis\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eDiscover how blockchains are disrupting the data world with this exciting title in the trusted \u003ci\u003eFor Dummies \u003c\/i\u003eline!\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIntroduction\u003c\/b\u003e\u003cb\u003e 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAbout This Book 1\u003c\/p\u003e \u003cp\u003eFoolish Assumptions 2\u003c\/p\u003e \u003cp\u003eIcons Used in This Book 2\u003c\/p\u003e \u003cp\u003eBeyond the Book 2\u003c\/p\u003e \u003cp\u003eWhere to Go from Here 3\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 1: Intro to Analytics and Blockchain 5\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1: Driving Business with Data and Analytics \u003c\/b\u003e\u003cb\u003e7\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDeriving Value from Data 8\u003c\/p\u003e \u003cp\u003eMonetizing data 8\u003c\/p\u003e \u003cp\u003eExchanging data 9\u003c\/p\u003e \u003cp\u003eVerifying data 10\u003c\/p\u003e \u003cp\u003eUnderstanding and Satisfying Regulatory Requirements 11\u003c\/p\u003e \u003cp\u003eClassifying individuals 11\u003c\/p\u003e \u003cp\u003eIdentifying criminals 11\u003c\/p\u003e \u003cp\u003eExamining common privacy laws 12\u003c\/p\u003e \u003cp\u003ePredicting Future Outcomes with Data 13\u003c\/p\u003e \u003cp\u003eClassifying entities 13\u003c\/p\u003e \u003cp\u003ePredicting behavior 14\u003c\/p\u003e \u003cp\u003eMaking decisions based on models 16\u003c\/p\u003e \u003cp\u003eChanging Business Practices to Create Desired Outcomes 16\u003c\/p\u003e \u003cp\u003eDefining the desired outcome 17\u003c\/p\u003e \u003cp\u003eBuilding models for simulation 17\u003c\/p\u003e \u003cp\u003eAligning operations and assessing results 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2: Digging into Blockchain Technology\u003c\/b\u003e\u003cb\u003e 19\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eExploring the Blockchain Landscape 20\u003c\/p\u003e \u003cp\u003eManaging ownership transfer 20\u003c\/p\u003e \u003cp\u003eDoing more with blockchain 21\u003c\/p\u003e \u003cp\u003eUnderstanding blockchain technology 21\u003c\/p\u003e \u003cp\u003eReviewing blockchain’s family tree 22\u003c\/p\u003e \u003cp\u003eFitting blockchain into today’s businesses 25\u003c\/p\u003e \u003cp\u003eUnderstanding Primary Blockchain Types 27\u003c\/p\u003e \u003cp\u003eCategorizing blockchain implementations 27\u003c\/p\u003e \u003cp\u003eDescribing basic blockchain type features 29\u003c\/p\u003e \u003cp\u003eContrasting popular enterprise blockchain implementations 30\u003c\/p\u003e \u003cp\u003eAligning Blockchain Features with Business Requirements 31\u003c\/p\u003e \u003cp\u003eReviewing blockchain core features 31\u003c\/p\u003e \u003cp\u003eExamining primary common business requirements 33\u003c\/p\u003e \u003cp\u003eMatching blockchain features to business requirements 34\u003c\/p\u003e \u003cp\u003eExamining Blockchain Use Cases 35\u003c\/p\u003e \u003cp\u003eManaging physical items in cyberspace 35\u003c\/p\u003e \u003cp\u003eHandling sensitive information 36\u003c\/p\u003e \u003cp\u003eConducting financial transactions 37\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3: Identifying Blockchain Data with Value\u003c\/b\u003e\u003cb\u003e 39\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eExploring Blockchain Data 40\u003c\/p\u003e \u003cp\u003eUnderstanding what’s stored in blockchain blocks 40\u003c\/p\u003e \u003cp\u003eRecording transaction data 41\u003c\/p\u003e \u003cp\u003eDissecting the parts of a block 43\u003c\/p\u003e \u003cp\u003eDecoding block data 47\u003c\/p\u003e \u003cp\u003eCategorizing Common Data in a Blockchain 49\u003c\/p\u003e \u003cp\u003eSerializing transaction data 49\u003c\/p\u003e \u003cp\u003eLogging events on the blockchain 50\u003c\/p\u003e \u003cp\u003eStoring value with smart contracts 52\u003c\/p\u003e \u003cp\u003eExamining Types of Blockchain Data for Value 52\u003c\/p\u003e \u003cp\u003eExploring basic transaction data 53\u003c\/p\u003e \u003cp\u003eAssociating real-world meaning to events 53\u003c\/p\u003e \u003cp\u003eAligning Blockchain Data with Real-World Processes 54\u003c\/p\u003e \u003cp\u003eUnderstanding smart contract functions 55\u003c\/p\u003e \u003cp\u003eAssessing smart contract event logs 55\u003c\/p\u003e \u003cp\u003eRanking transaction and event data by its effect 55\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4: Implementing Blockchain Analytics in Business\u003c\/b\u003e\u003cb\u003e 57\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAligning Analytics with Business Goals 58\u003c\/p\u003e \u003cp\u003eLeveraging newly accessible decentralized tools 58\u003c\/p\u003e \u003cp\u003eMonetizing data 59\u003c\/p\u003e \u003cp\u003eExchanging and integrating data effectively 59\u003c\/p\u003e \u003cp\u003eSurveying Options for Your Analytics Lab 60\u003c\/p\u003e \u003cp\u003eInstalling the Blockchain Client 61\u003c\/p\u003e \u003cp\u003eInstalling the Test Blockchain 65\u003c\/p\u003e \u003cp\u003eInstalling the Testing Environment 68\u003c\/p\u003e \u003cp\u003eGetting ready to install Truffle 69\u003c\/p\u003e \u003cp\u003eDownloading and installing Truffle 72\u003c\/p\u003e \u003cp\u003eInstalling the IDE 74\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5: Interacting with Blockchain Data \u003c\/b\u003e\u003cb\u003e79\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eExploring the Blockchain Analytics Ecosystem 80\u003c\/p\u003e \u003cp\u003eReviewing your blockchain lab 80\u003c\/p\u003e \u003cp\u003eIdentifying analytics client options 81\u003c\/p\u003e \u003cp\u003eChoosing the best blockchain analytics client 83\u003c\/p\u003e \u003cp\u003eAdding Anaconda and Web3.js to Your Lab 84\u003c\/p\u003e \u003cp\u003eVerifying platform prerequisites 84\u003c\/p\u003e \u003cp\u003eInstalling the Anaconda platform 86\u003c\/p\u003e \u003cp\u003eInstalling the Web3.py library 89\u003c\/p\u003e \u003cp\u003eSetting up your blockchain analytics project 90\u003c\/p\u003e \u003cp\u003eWriting a Python Script to Access a Blockchain 92\u003c\/p\u003e \u003cp\u003eInterfacing with smart contracts 93\u003c\/p\u003e \u003cp\u003eFinding a smart contract’s ABI 94\u003c\/p\u003e \u003cp\u003eBuilding a Local Blockchain to Analyze 100\u003c\/p\u003e \u003cp\u003eConnecting to your blockchain 101\u003c\/p\u003e \u003cp\u003eInvoking smart contract functions 101\u003c\/p\u003e \u003cp\u003eFetching blockchain data 102\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 2: Fetching Blockchain Chain 105\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6: Parsing Blockchain Data and Building the Analysis Dataset\u003c\/b\u003e\u003cb\u003e 107\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eComparing On-Chain and External Analysis Options 108\u003c\/p\u003e \u003cp\u003eConsidering access speed 108\u003c\/p\u003e \u003cp\u003eComparing one-off versus repeated analysis 109\u003c\/p\u003e \u003cp\u003eAssessing data completeness 110\u003c\/p\u003e \u003cp\u003eIntegrating External Data 111\u003c\/p\u003e \u003cp\u003eDetermining what data you need 112\u003c\/p\u003e \u003cp\u003eExtending identities to off-chain data 113\u003c\/p\u003e \u003cp\u003eFinding external data 114\u003c\/p\u003e \u003cp\u003eIdentifying Features 115\u003c\/p\u003e \u003cp\u003eDescribing how features affect outcomes 116\u003c\/p\u003e \u003cp\u003eComparing filtering and wrapping methods 116\u003c\/p\u003e \u003cp\u003eBuilding an Analysis Dataset 117\u003c\/p\u003e \u003cp\u003eConnecting to multiple data sources 118\u003c\/p\u003e \u003cp\u003eBuilding a cross-referenced dataset 118\u003c\/p\u003e \u003cp\u003eCleaning your data 118\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7: Building Basic Blockchain Analysis Models\u003c\/b\u003e\u003cb\u003e 121\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIdentifying Related Data 122\u003c\/p\u003e \u003cp\u003eGrouping data based on features (attributes) 123\u003c\/p\u003e \u003cp\u003eDetermining group membership 126\u003c\/p\u003e \u003cp\u003eDiscovering relationships among items 129\u003c\/p\u003e \u003cp\u003eMaking Predictions of Future Outcomes 130\u003c\/p\u003e \u003cp\u003eSelecting features that affect outcome 131\u003c\/p\u003e \u003cp\u003eBeating the best guess 133\u003c\/p\u003e \u003cp\u003eBuilding confidence 134\u003c\/p\u003e \u003cp\u003eAnalyzing Time-Series Data 135\u003c\/p\u003e \u003cp\u003eExploring growth and maturity 137\u003c\/p\u003e \u003cp\u003eIdentifying seasonal trends 138\u003c\/p\u003e \u003cp\u003eDescribing cycles of results 138\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8: Leveraging Advanced Blockchain Analysis Models\u003c\/b\u003e\u003cb\u003e 139\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIdentifying Participation Incentive Mechanisms 140\u003c\/p\u003e \u003cp\u003eComplying with mandates 141\u003c\/p\u003e \u003cp\u003ePlaying games with partners 141\u003c\/p\u003e \u003cp\u003eRewarding and punishing participants 142\u003c\/p\u003e \u003cp\u003eManaging Deployment and Maintenance Costs 143\u003c\/p\u003e \u003cp\u003eLowering the cost of admission 143\u003c\/p\u003e \u003cp\u003eLeveraging participation value 145\u003c\/p\u003e \u003cp\u003eAligning ROI with analytics currency 146\u003c\/p\u003e \u003cp\u003eCollaborating to Create Better Models 147\u003c\/p\u003e \u003cp\u003eCollecting data from a cohort 148\u003c\/p\u003e \u003cp\u003eBuilding models collaboratively 148\u003c\/p\u003e \u003cp\u003eAssessing model quality as a team 149\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 3: Analyzing and Visualizing Blockchain Analysis Data 151\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9: Identifying Clustered and Related Data\u003c\/b\u003e\u003cb\u003e 153\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAnalyzing Data Clustering Using Popular Models 154\u003c\/p\u003e \u003cp\u003eDelivering valuable knowledge with cluster analysis 154\u003c\/p\u003e \u003cp\u003eExamining popular clustering techniques 155\u003c\/p\u003e \u003cp\u003eUnderstanding k-means analysis 155\u003c\/p\u003e \u003cp\u003eEvaluating model effectiveness with diagnostics 160\u003c\/p\u003e \u003cp\u003eImplementing Blockchain Data Clustering Algorithms in Python 160\u003c\/p\u003e \u003cp\u003eDiscovering Association Rules in Data 163\u003c\/p\u003e \u003cp\u003eDelivering valuable knowledge with association rules analysis 163\u003c\/p\u003e \u003cp\u003eDescribing the apriori association rules algorithm 164\u003c\/p\u003e \u003cp\u003eEvaluating model effectiveness with diagnostics 167\u003c\/p\u003e \u003cp\u003eDetermining When to Use Clustering and Association Rules 168\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10: Classifying Blockchain Data\u003c\/b\u003e\u003cb\u003e 171\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAnalyzing Data Classification Using Popular Models 172\u003c\/p\u003e \u003cp\u003eDelivering valuable knowledge with classification analysis 172\u003c\/p\u003e \u003cp\u003eExamining popular classification techniques 173\u003c\/p\u003e \u003cp\u003eUnderstanding how the decision tree algorithm works 173\u003c\/p\u003e \u003cp\u003eUnderstanding how the naïve Bayes algorithm works 176\u003c\/p\u003e \u003cp\u003eEvaluating model effectiveness with diagnostics 178\u003c\/p\u003e \u003cp\u003eImplementing Blockchain Classification Algorithms in Python 179\u003c\/p\u003e \u003cp\u003eDefining model input data requirements 179\u003c\/p\u003e \u003cp\u003eBuilding your classification model dataset 181\u003c\/p\u003e \u003cp\u003eDeveloping your classification model code 184\u003c\/p\u003e \u003cp\u003eDetermining When Classification Fits Your Analytics Needs 188\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11: Predicting the Future with Regression\u003c\/b\u003e\u003cb\u003e 189\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAnalyzing Predictions and Relationships Using Popular Models 190\u003c\/p\u003e \u003cp\u003eDelivering valuable knowledge with regression analysis 190\u003c\/p\u003e \u003cp\u003eExamining popular regression techniques 191\u003c\/p\u003e \u003cp\u003eDescribing how linear regression works 195\u003c\/p\u003e \u003cp\u003eDescribing how logistic regression works 198\u003c\/p\u003e \u003cp\u003eEvaluating model effectiveness with diagnostics 201\u003c\/p\u003e \u003cp\u003eImplementing Regression Algorithms in Python 203\u003c\/p\u003e \u003cp\u003eDefining model input data requirements 203\u003c\/p\u003e \u003cp\u003eBuilding your regression model dataset 203\u003c\/p\u003e \u003cp\u003eDeveloping your regression model code 204\u003c\/p\u003e \u003cp\u003eDetermining When Regression Fits Your Analytics Needs 207\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12: Analyzing Blockchain Data over Time\u003c\/b\u003e\u003cb\u003e 209\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAnalyzing Time Series Data Using Popular Models 210\u003c\/p\u003e \u003cp\u003eDelivering valuable knowledge with time series analysis 211\u003c\/p\u003e \u003cp\u003eExamining popular time series techniques 211\u003c\/p\u003e \u003cp\u003eVisualizing time series results 214\u003c\/p\u003e \u003cp\u003eImplementing Time Series Algorithms in Python 216\u003c\/p\u003e \u003cp\u003eDefining model input data requirements 217\u003c\/p\u003e \u003cp\u003eDeveloping your time series model code 219\u003c\/p\u003e \u003cp\u003eDetermining When Time Series Fits Your Analytics Needs 221\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 4: Implementing Blockchain Analysis Models 223\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13: Writing Models from Scratch\u003c\/b\u003e\u003cb\u003e 225\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eInteracting with Blockchains 226\u003c\/p\u003e \u003cp\u003eConnecting to a Blockchain 226\u003c\/p\u003e \u003cp\u003eUsing an application programming interface to interact with a blockchain 228\u003c\/p\u003e \u003cp\u003eReading from a blockchain 230\u003c\/p\u003e \u003cp\u003eUpdating previously read blockchain data 234\u003c\/p\u003e \u003cp\u003eExamining Blockchain Client Languages and Approaches 236\u003c\/p\u003e \u003cp\u003eIntroducing popular blockchain client programming languages 237\u003c\/p\u003e \u003cp\u003eComparing popular language pros and cons 238\u003c\/p\u003e \u003cp\u003eDeciding on the right language 238\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14: Calling on Existing Frameworks\u003c\/b\u003e\u003cb\u003e 239\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBenefitting from Standardization 240\u003c\/p\u003e \u003cp\u003eEasing the burden of compliance 240\u003c\/p\u003e \u003cp\u003eAvoiding inefficient code 242\u003c\/p\u003e \u003cp\u003eRaising the bar on quality 244\u003c\/p\u003e \u003cp\u003eFocusing on Analytics, Not Utilities 245\u003c\/p\u003e \u003cp\u003eAvoiding feature bloat 245\u003c\/p\u003e \u003cp\u003eSetting granular goals 246\u003c\/p\u003e \u003cp\u003eManaging post-operational models 247\u003c\/p\u003e \u003cp\u003eLeveraging the Efforts of Others 248\u003c\/p\u003e \u003cp\u003eDeciding between make or buy 248\u003c\/p\u003e \u003cp\u003eScoping your testing efforts 249\u003c\/p\u003e \u003cp\u003eAligning personnel expertise with tasks 250\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 15: Using Third-Party Toolsets and Frameworks\u003c\/b\u003e\u003cb\u003e 251\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSurveying Toolsets and Frameworks 252\u003c\/p\u003e \u003cp\u003eDescribing TensorFlow 253\u003c\/p\u003e \u003cp\u003eExamining Keras 255\u003c\/p\u003e \u003cp\u003eLooking at PyTorch 256\u003c\/p\u003e \u003cp\u003eSupercharging PyTorch with fast.ai 258\u003c\/p\u003e \u003cp\u003ePresenting Apache MXNet 260\u003c\/p\u003e \u003cp\u003eIntroducing Caffe 261\u003c\/p\u003e \u003cp\u003eDescribing Deeplearning4j 262\u003c\/p\u003e \u003cp\u003eComparing Toolsets and Frameworks 264\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 16: Putting It All Together\u003c\/b\u003e\u003cb\u003e 267\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAssessing Your Analytics Needs 268\u003c\/p\u003e \u003cp\u003eDescribing the project’s purpose 268\u003c\/p\u003e \u003cp\u003eDefining the process 270\u003c\/p\u003e \u003cp\u003eTaking inventory of resources 271\u003c\/p\u003e \u003cp\u003eChoosing the Best Fit 273\u003c\/p\u003e \u003cp\u003eUnderstanding personnel skills and affinity 273\u003c\/p\u003e \u003cp\u003eLeveraging infrastructure 275\u003c\/p\u003e \u003cp\u003eIntegrating into organizational culture 276\u003c\/p\u003e \u003cp\u003eEmbracing iteration 276\u003c\/p\u003e \u003cp\u003eManaging the Blockchain Project 277\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 5: The Part of Tens 279\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 17: Ten Tools for Developing Blockchain Analytics Models\u003c\/b\u003e\u003cb\u003e 281\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDeveloping Analytics Models with Anaconda 282\u003c\/p\u003e \u003cp\u003eWriting Code in Visual Studio Code 283\u003c\/p\u003e \u003cp\u003ePrototyping Analytics Models with Jupyter 284\u003c\/p\u003e \u003cp\u003eDeveloping Models in the R Language with RStudio 285\u003c\/p\u003e \u003cp\u003eInteracting with Blockchain Data with web3.py 287\u003c\/p\u003e \u003cp\u003eExtract Blockchain Data to a Database 288\u003c\/p\u003e \u003cp\u003eExtracting blockchain data with EthereumDB 288\u003c\/p\u003e \u003cp\u003eStoring blockchain data in a database using Ethereum-etl 288\u003c\/p\u003e \u003cp\u003eAccessing Ethereum Networks at Scale with Infura 289\u003c\/p\u003e \u003cp\u003eAnalyzing Very Large Datasets in Python with Vaex 290\u003c\/p\u003e \u003cp\u003eExamining Blockchain Data 291\u003c\/p\u003e \u003cp\u003eExploring Ethereum with Etherscan.io 291\u003c\/p\u003e \u003cp\u003ePerusing multiple blockchains with Blockchain.com 292\u003c\/p\u003e \u003cp\u003eViewing cryptocurrency details with ColossusXT 293\u003c\/p\u003e \u003cp\u003ePreserving Privacy in Blockchain Analytics with MADANA 293\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 18: Ten Tips for Visualizing Data\u003c\/b\u003e\u003cb\u003e 295\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChecking the Landscape around You 296\u003c\/p\u003e \u003cp\u003eLeveraging the Community 297\u003c\/p\u003e \u003cp\u003eMaking Friends with Network Visualizations 298\u003c\/p\u003e \u003cp\u003eRecognizing Subjectivity 299\u003c\/p\u003e \u003cp\u003eUsing Scale, Text, and the Information You Need 300\u003c\/p\u003e \u003cp\u003eConsidering Frequent Updates for Volatile Blockchain Data 301\u003c\/p\u003e \u003cp\u003eGetting Ready for Big Data 302\u003c\/p\u003e \u003cp\u003eProtecting Privacy 302\u003c\/p\u003e \u003cp\u003eTelling Your Story 303\u003c\/p\u003e \u003cp\u003eChallenging Yourself! 303\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 19: Ten Uses for Blockchain Analytics\u003c\/b\u003e\u003cb\u003e 305\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAccessing Public Financial Transaction Data 306\u003c\/p\u003e \u003cp\u003eConnecting with the Internet of Things (IoT) 307\u003c\/p\u003e \u003cp\u003eEnsuring Data and Document Authenticity 308\u003c\/p\u003e \u003cp\u003eControlling Secure Document Integrity 308\u003c\/p\u003e \u003cp\u003eTracking Supply Chain Items 310\u003c\/p\u003e \u003cp\u003eEmpowering Predictive Analytics 310\u003c\/p\u003e \u003cp\u003eAnalyzing Real-Time Data 311\u003c\/p\u003e \u003cp\u003eSupercharging Business Strategy 312\u003c\/p\u003e \u003cp\u003eManaging Data Sharing 312\u003c\/p\u003e \u003cp\u003eStandardizing Collaboration Forms 312\u003c\/p\u003e \u003cp\u003eIndex 315\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eMichael G. Solomon, PhD,\u003c\/b\u003e is a professor at the University of the Cumberlands who specializes in courses on blockchain and distributed computing systems as well as computer security. He holds numerous security and project management certifications and has written several books on security and project management, including \u003ci\u003eEthereum For Dummies.\u003c\/i\u003e   \u003c\/p\u003e\u003cul\u003e \u003cli\u003eDiscover how blockchains are disrupting the data world\u003c\/li\u003e \u003cli\u003eBuild models that classify, predict, and analyze data\u003c\/li\u003e \u003cli\u003eUse analytics models to solve business problems\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cb\u003eBe on the cutting edge with blockchain\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eBlockchain is about to upend the world of data analytics just as it did financial record-keeping. Here's what you need to become an early adopter of blockchain as a big-data tool! Explore how blockchains store data and learn how this rich new source of data can enhance predictive analytics and real-time data analysis. You'll also find out how blockchains can help you manage your data and keep shared data more secure. Learn to implement blockchain analysis models, use third-party toolsets, assess your analysis needs, and more. \u003c\/p\u003e\u003cp\u003e\u003cb\u003eInside...\u003c\/b\u003e \u003c\/p\u003e\u003cul\u003e \u003cli\u003eExplore blockchain technologies\u003c\/li\u003e \u003cli\u003eLook at existing use cases\u003c\/li\u003e \u003cli\u003eExamine analytics capabilities  for blockchain data\u003c\/li\u003e \u003cli\u003eInteract with blockchain data\u003c\/li\u003e \u003cli\u003eMine data for results\u003c\/li\u003e \u003cli\u003eBuild analytics models\u003c\/li\u003e \u003cli\u003eCreate visual representations\u003c\/li\u003e \u003c\/ul\u003e","brand":"For Dummies","offers":[{"title":"Default Title","offer_id":47988847739109,"sku":"NP9781119651772","price":29.99,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119651772.jpg?v=1761781758","url":"https:\/\/k12savings.com\/products\/blockchain-data-analytics-for-dummies-isbn-9781119651772","provider":"K12savings","version":"1.0","type":"link"}