Practical Data Science With Sap

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Practical Data Science with SAP

Greg Foss,Paul Modderman

Author : Greg Foss,Paul Modderman
Publisher : O'Reilly Media
Page : 333 pages
File Size : 51,6 Mb
Release : 2019-09-18
Category : Computers
ISBN : 9781492046417

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Practical Data Science with SAP by Greg Foss,Paul Modderman Pdf

Learn how to fuse today's data science tools and techniques with your SAP enterprise resource planning (ERP) system. With this practical guide, SAP veterans Greg Foss and Paul Modderman demonstrate how to use several data analysis tools to solve interesting problems with your SAP data. Data engineers and scientists will explore ways to add SAP data to their analysis processes, while SAP business analysts will learn practical methods for answering questions about the business. By focusing on grounded explanations of both SAP processes and data science tools, this book gives data scientists and business analysts powerful methods for discovering deep data truths. You'll explore: Examples of how data analysis can help you solve several SAP challenges Natural language processing for unlocking the secrets in text Data science techniques for data clustering and segmentation Methods for detecting anomalies in your SAP data Data visualization techniques for making your data come to life

Practical Data Science with SAP

Greg Foss,Paul Modderman

Author : Greg Foss,Paul Modderman
Publisher : Unknown
Page : 330 pages
File Size : 44,5 Mb
Release : 2019
Category : Business enterprises
ISBN : 1492046434

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Practical Data Science with SAP by Greg Foss,Paul Modderman Pdf

With Early Release ebooks, you get books in their earliest form-the author's raw and unedited content as he or she writes-so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released. Learn how to fuse today's data science tools and techniques with your SAP enterprise resource planning (ERP) system. With this practical guide, SAP veterans Greg Foss and Paul Modderman demonstrate how to use several data analysis tools to solve interesting problems with your SAP data. Data engineers and scientists will explore ways to add SAP data to their analysis processes, while SAP business analysts will learn practical methods for answering questions about the business.

Practical Guide to SAP HANA and Big Data Analytics

Dominique Alfermann,Stefan Hartmann

Author : Dominique Alfermann,Stefan Hartmann
Publisher : Espresso Tutorials GmbH
Page : 235 pages
File Size : 41,6 Mb
Release : 2018-12-20
Category : Electronic
ISBN : 9783960128649

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Practical Guide to SAP HANA and Big Data Analytics by Dominique Alfermann,Stefan Hartmann Pdf

In this book written for SAP BI, big data, and IT architects, the authors expertly provide clear recommendations for building modern analytics architectures running on SAP HANA technologies. Explore integration with big data frameworks and predictive analytics components. Obtain the tools you need to assess possible architecture scenarios and get guidelines for choosing the best option for your organization. Know your options for on-premise, in the cloud, and hybrid solutions. Readers will be guided through SAP BW/4HANA and SAP HANA native data warehouse scenarios, as well as field-tested integration options with big data platforms. Explore migration options and architecture best practices. Consider organizational and procedural changes resulting from the move to a new, up-to-date analytics architecture that supports your data-driven or data-informed organization. By using practical examples, tips, and screenshots, this book explores: - SAP HANA and SAP BW/4HANA architecture concepts - Predictive Analytics and Big Data component integration - Recommendations for a sustainable, future-proof analytics solutions - Organizational impact and change management

Practical Data Science

Andreas François Vermeulen

Author : Andreas François Vermeulen
Publisher : Apress
Page : 821 pages
File Size : 43,5 Mb
Release : 2018-02-21
Category : Computers
ISBN : 9781484230541

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Practical Data Science by Andreas François Vermeulen Pdf

Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets. The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions. What You'll Learn Become fluent in the essential concepts and terminology of data science and data engineering Build and use a technology stack that meets industry criteria Master the methods for retrieving actionable business knowledge Coordinate the handling of polyglot data types in a data lake for repeatable results Who This Book Is For Data scientists and data engineers who are required to convert data from a data lake into actionable knowledge for their business, and students who aspire to be data scientists and data engineers

Practical Data Analysis

Hector Cuesta,Dr. Sampath Kumar

Author : Hector Cuesta,Dr. Sampath Kumar
Publisher : Packt Publishing Ltd
Page : 338 pages
File Size : 43,8 Mb
Release : 2016-09-30
Category : Computers
ISBN : 9781785286667

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Practical Data Analysis by Hector Cuesta,Dr. Sampath Kumar Pdf

A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.

Data Science for Business

Foster Provost,Tom Fawcett

Author : Foster Provost,Tom Fawcett
Publisher : "O'Reilly Media, Inc."
Page : 414 pages
File Size : 53,9 Mb
Release : 2013-07-27
Category : Computers
ISBN : 9781449374280

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Data Science for Business by Foster Provost,Tom Fawcett Pdf

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates

Practical Data Analytics for Innovation in Medicine

Gary D. Miner,Linda A. Miner,Scott Burk,Mitchell Goldstein,Robert Nisbet,Nephi Walton,Thomas Hill

Author : Gary D. Miner,Linda A. Miner,Scott Burk,Mitchell Goldstein,Robert Nisbet,Nephi Walton,Thomas Hill
Publisher : Academic Press
Page : 578 pages
File Size : 47,5 Mb
Release : 2023-02-08
Category : Computers
ISBN : 9780323952750

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Practical Data Analytics for Innovation in Medicine by Gary D. Miner,Linda A. Miner,Scott Burk,Mitchell Goldstein,Robert Nisbet,Nephi Walton,Thomas Hill Pdf

Practical Data Analytics for Innovation in Medicine: Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies, Second Edition discusses the needs of healthcare and medicine in the 21st century, explaining how data analytics play an important and revolutionary role. With healthcare effectiveness and economics facing growing challenges, there is a rapidly emerging movement to fortify medical treatment and administration by tapping the predictive power of big data, such as predictive analytics, which can bolster patient care, reduce costs, and deliver greater efficiencies across a wide range of operational functions. Sections bring a historical perspective, highlight the importance of using predictive analytics to help solve health crisis such as the COVID-19 pandemic, provide access to practical step-by-step tutorials and case studies online, and use exercises based on real-world examples of successful predictive and prescriptive tools and systems. The final part of the book focuses on specific technical operations related to quality, cost-effective medical and nursing care delivery and administration brought by practical predictive analytics. Brings a historical perspective in medical care to discuss both the current status of health care delivery worldwide and the importance of using modern predictive analytics to help solve the health care crisis Provides online tutorials on several predictive analytics systems to help readers apply their knowledge on today’s medical issues and basic research Teaches how to develop effective predictive analytic research and to create decisioning/prescriptive analytic systems to make medical decisions quicker and more accurate

Practical Data Science Cookbook

Prabhanjan Tattar,Tony Ojeda,Sean Patrick Murphy,Benjamin Bengfort,Abhijit Dasgupta

Author : Prabhanjan Tattar,Tony Ojeda,Sean Patrick Murphy,Benjamin Bengfort,Abhijit Dasgupta
Publisher : Packt Publishing Ltd
Page : 428 pages
File Size : 44,7 Mb
Release : 2017-06-29
Category : Computers
ISBN : 9781787123267

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Practical Data Science Cookbook by Prabhanjan Tattar,Tony Ojeda,Sean Patrick Murphy,Benjamin Bengfort,Abhijit Dasgupta Pdf

Over 85 recipes to help you complete real-world data science projects in R and Python About This Book Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data Get beyond the theory and implement real-world projects in data science using R and Python Easy-to-follow recipes will help you understand and implement the numerical computing concepts Who This Book Is For If you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python. What You Will Learn Learn and understand the installation procedure and environment required for R and Python on various platforms Prepare data for analysis by implement various data science concepts such as acquisition, cleaning and munging through R and Python Build a predictive model and an exploratory model Analyze the results of your model and create reports on the acquired data Build various tree-based methods and Build random forest In Detail As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don't. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python. Style and approach This step-by-step guide to data science is full of hands-on examples of real-world data science tasks. Each recipe focuses on a particular task involved in the data science pipeline, ranging from readying the dataset to analytics and visualization

Practical Data Science with Hadoop and Spark

Ofer Mendelevitch,Casey Stella,Douglas Eadline

Author : Ofer Mendelevitch,Casey Stella,Douglas Eadline
Publisher : Addison-Wesley Professional
Page : 463 pages
File Size : 52,8 Mb
Release : 2016-12-08
Category : Computers
ISBN : 9780134029726

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Practical Data Science with Hadoop and Spark by Ofer Mendelevitch,Casey Stella,Douglas Eadline Pdf

The Complete Guide to Data Science with Hadoop—For Technical Professionals, Businesspeople, and Students Demand is soaring for professionals who can solve real data science problems with Hadoop and Spark. Practical Data Science with Hadoop® and Spark is your complete guide to doing just that. Drawing on immense experience with Hadoop and big data, three leading experts bring together everything you need: high-level concepts, deep-dive techniques, real-world use cases, practical applications, and hands-on tutorials. The authors introduce the essentials of data science and the modern Hadoop ecosystem, explaining how Hadoop and Spark have evolved into an effective platform for solving data science problems at scale. In addition to comprehensive application coverage, the authors also provide useful guidance on the important steps of data ingestion, data munging, and visualization. Once the groundwork is in place, the authors focus on specific applications, including machine learning, predictive modeling for sentiment analysis, clustering for document analysis, anomaly detection, and natural language processing (NLP). This guide provides a strong technical foundation for those who want to do practical data science, and also presents business-driven guidance on how to apply Hadoop and Spark to optimize ROI of data science initiatives. Learn What data science is, how it has evolved, and how to plan a data science career How data volume, variety, and velocity shape data science use cases Hadoop and its ecosystem, including HDFS, MapReduce, YARN, and Spark Data importation with Hive and Spark Data quality, preprocessing, preparation, and modeling Visualization: surfacing insights from huge data sets Machine learning: classification, regression, clustering, and anomaly detection Algorithms and Hadoop tools for predictive modeling Cluster analysis and similarity functions Large-scale anomaly detection NLP: applying data science to human language

Practical Data Analytics for BFSI

Bharat Sikka,Dr. Priyender Yadav,Dr. Prashant Verma

Author : Bharat Sikka,Dr. Priyender Yadav,Dr. Prashant Verma
Publisher : Orange Education Pvt Ltd
Page : 356 pages
File Size : 49,6 Mb
Release : 2023-09-02
Category : Computers
ISBN : 9789388590907

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Practical Data Analytics for BFSI by Bharat Sikka,Dr. Priyender Yadav,Dr. Prashant Verma Pdf

Revolutionizing BFSI with Data Analytics KEY FEATURES ● Real-world examples and exercises will ground you in the practical application of analytics techniques specific to BFSI. ● Master Python for essential coding, SQL for data manipulation, and industry-leading tools like IBM SPSS and Power BI for sophisticated analyses. ● Understand how data-driven strategies generate profits, mitigate risks, and redefine customer support dynamics within the BFSI sphere. DESCRIPTION Are you looking to unlock the transformative potential of data analytics in the dynamic world of Banking, Financial Services, and Insurance (BFSI)? This book is your essential guide to mastering the intricate interplay of data science and analytics that underpins the BFSI landscape. Designed for intermediate-level practitioners, as well as those aspiring to join the ranks of BFSI analytics professionals, this book is your compass in the data-driven realm of banking. Address the unique challenges and opportunities of the BFSI sector using Artificial Intelligence and Machine Learning models for a data driven analysis. This book is a step by step guide to utilize tools like IBM SPSS and Microsoft Power BI. Hands-on examples that utilize Python and SQL programming languages make this an essential guide. The book features numerous case studies that illuminate various use cases of Analytics in BFSI. Each chapter is enriched with practical insights and concludes with a valuable multiple-choice questionnaire, reinforcing understanding and engagement. This book will uncover how these solutions not only pave the way for increased profitability but also navigate risks with precision and elevate customer support to unparalleled heights. WHAT WILL YOU LEARN ● Delve into the world of Data Science, including Artificial Intelligence and Machine Learning, with a focus on their application within BFSI. ● Explore hands-on examples and step-by-step tutorials that provide practical solutions to real-world challenges faced by banking institutions. ● Develop skills in essential programming languages such as Python (fundamentals) and SQL (intermediate), crucial for effective data manipulation and analysis. ● Gain insights into how businesses adapt data-driven strategies to make informed decisions, leading to improved operational efficiency. ● Stay updated on emerging trends, technologies, and innovations shaping the future of data analytics in the BFSI industry. WHO IS THIS BOOK FOR? This book is tailored for professionals already engaged in or seeking roles within Data Analytics in the BFSI industry. Additionally, it serves as a strategic resource for business leaders and upper management, guiding them in shaping data platforms and products within their organizations. The book also serves as a starting point for individuals interested in the BFSI sector. Prior experience with coding tools such as Python, SQL, Power BI is beneficial but not required as it covers all dimensions from the basics. TABLE OF CONTENTS 1. Introduction to BFSI and Data Driven Banking 2. Introduction to Analytics and Data Science 3. Major Areas of Analytics Utilization 4. Understanding Infrastructures behind BFSI for Analytics 5. Data Governance and AI/ML Model Governance in BFSI 6. Domains of BFSI and team planning 7. Customer Demographic Analysis and Customer Segmentation 8. Text Mining and Social Media Analytics 9. Lead Generation Through Analytical Reasoning and Machine Learning 10. Cross Sell and Up Sell of Products through Machine Learning 11. Pricing Optimization 12. Data Envelopment Analysis 13. ATM Cash Forecasting 14. Unstructured Data Analytics 15. Fraud Modelling 16. Detection of Money Laundering and Analysis 17. Credit Risk and Stressed Assets 18. High Performance Architectures: On-Premises and Cloud 19. Growing Trends in the Data-Driven Future of BFSI

SAP Data Intelligence

Dharma Teja Atluri,Devraj Bardhan,Santanu Ghosh,Snehasish Ghosh,Arindom Saha

Author : Dharma Teja Atluri,Devraj Bardhan,Santanu Ghosh,Snehasish Ghosh,Arindom Saha
Publisher : SAP PRESS
Page : 783 pages
File Size : 41,6 Mb
Release : 2021
Category : Computers
ISBN : 1493221620

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SAP Data Intelligence by Dharma Teja Atluri,Devraj Bardhan,Santanu Ghosh,Snehasish Ghosh,Arindom Saha Pdf

Manage your data landscape with SAP Data Intelligence! Begin by understanding its architecture and capabilities and then see how to set up and install SAP Data Intelligence with step-by-step instructions. Walk through SAP Data Intelligence applications and learn how to use them for data governance, orchestration, and machine learning. Integrate with ABAP-based systems, SAP Vora, SAP Analytics Cloud, and more. Manage, secure, and operate SAP Data Intelligence with this all-in-one guide!In this book, you'll learn about:a. Configuration Build your SAP Data Intelligence landscape! Use SAP Cloud Appliance Library for cloud deployment, including provisioning, sizing, and accessing the launchpad. Perform on-premise installations using tools like the maintenance planner. b. Capabilities Put the core capabilities of SAP Data Intelligence to work! Manage and govern your data with the metadata explorer, use the modeler application to create data processing pipelines, create apps with the Jupyter Notebook, and more. c. Integration and Administration Integrate, manage, and operate SAP Data Intelligence! Get step-by-step instructions for integration with SAP and non-SAP systems. Learn about key administration tasks and make sure your landscape is secure and running smoothly. Highlights include:1) Configuration and installation2) Data governance3) Data processing pipelines4) Docker images5) ML Scenario Manager6) Jupyter Notebook7) Python SDK8) Integration9) Administration10) Security11) Application lifecycle management12) Use cases

A Practical Guide to SAP Data Warehouse Cloud

Klaus-Peter Sauer

Author : Klaus-Peter Sauer
Publisher : Espresso Tutorials GmbH
Page : 279 pages
File Size : 51,5 Mb
Release : 2022-07-28
Category : Computers
ISBN : 9783960121268

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A Practical Guide to SAP Data Warehouse Cloud by Klaus-Peter Sauer Pdf

Learn about the advantages of SAP Data Warehouse Cloud (DWC): from data management all the way through to visualization, this book covers all the tools you need to set up a modern, cloud-based data warehouse landscape. You can even set up hybrid architectures or convert on-premise SAP BW systems to the SAP BW Bridge. Operating departments will learn how they can use virtual work areas (spaces) to enrich central corporate data with local data without having to copy data or download files. New findings can be easily shared with others. For IT employees in particular, there is an extensive introduction to modeling and the Data Builder. With the editors and functionalities of this tool, you get to know the technical implementation of data modeling in more detail. In addition, the Business Builder offers professional users a simplified analysis of data by reducing the time required for semantic modeling and enrichment of data. After discussing important aspects of the configuration and security of SAP Data Warehouse Cloud, the author looks at the developments that can be expected for this highly dynamic topic in the future. - Basic principles of SAP Data Warehouse Cloud - Virtual interaction between operating departments and IT via spaces - Separation of semantic modeling and the data layer - SAP BW Bridge and Hybrid landscapes

SAP HANA 2.0

Denys Van Kempen

Author : Denys Van Kempen
Publisher : SAP PRESS
Page : 438 pages
File Size : 40,5 Mb
Release : 2019
Category : Computers
ISBN : 1493218387

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SAP HANA 2.0 by Denys Van Kempen Pdf

Enter the fast-paced world of SAP HANA 2.0 with this introductory guide. Begin with an exploration of the technological backbone of SAP HANA as a database and platform. Then, step into key SAP HANA user roles and discover core capabilities for administration, application development, advanced analytics, security, data integration, and more. No matter how SAP HANA 2.0 fits into your business, this book is your starting point. In this book, you'll learn about: a. Technology Discover what makes an in-memory database platform. Learn about SAP HANA's journey from version 1.0 to 2.0, take a tour of your technology options, and walk through deployment scenarios and implementation requirements. b. Tools Unpack your SAP HANA toolkit. See essential tools in action, from SAP HANA cockpit and SAP HANA studio, to the SAP HANA Predictive Analytics Library and SAP HANA smart data integration. c. Key Roles Understand how to use SAP HANA as a developer, administrator, data scientist, data center architect, and more. Explore key tasks like backend programming with SQLScript, security setup with roles and authorizations, data integration with the SAP HANA Data Management Suite, and more. Highlights include: 1) Architecture 2) Administration 3) Application development 4) Analytics 5) Security 6) Data integration 7) Data architecture 8) Data center

SAP Data Services

Bing Chen,James Hanck,Patrick Hanck,Scott Hertel,Allen Lissarrague,Paul Médaille

Author : Bing Chen,James Hanck,Patrick Hanck,Scott Hertel,Allen Lissarrague,Paul Médaille
Publisher : SAP PRESS
Page : 0 pages
File Size : 46,6 Mb
Release : 2015
Category : Business enterprises
ISBN : 1493211676

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SAP Data Services by Bing Chen,James Hanck,Patrick Hanck,Scott Hertel,Allen Lissarrague,Paul Médaille Pdf

It's time to extract, transform, and load your skills on managing enterprise data With this book on SAP Data Services, you'll be an expert in no time. After learning about topics like planning, blueprinting, and integrating SAP Data Services, you'll get into the core of the book - detailed steps on how to perform Data Services tasks. Get the skills you need for your daily job, from basic tasks like designing objects, to advanced duties like analyzing unstructured text. Starting with Data Services Set up your Data Services foundation. Learn how to plan for Data Services in your organization, then how to install, configure, and get working with it. Data Services Tasks Regardless of your skillset, you'll find essential information on the tasks you'll encounter when working with Data Services. Learn how to architect jobs with performance, transparency, supportability, and cost in mind. Integration Data Services plays well with others. This book explores two common integration scenarios: data warehousing and retail environments. Learn how to overcome common challenges and see frequently used scenarios. Highlights: Data Services architecture and OS Enterprise information management Installation: Windows and Linux Configuration Troubleshooting Data Services objects Datastores Data Services scripting language Social media analytics Information Steward Integration: data warehousing and retail

Software Engineering for Data Scientists

Catherine Nelson

Author : Catherine Nelson
Publisher : "O'Reilly Media, Inc."
Page : 248 pages
File Size : 48,9 Mb
Release : 2024-04-16
Category : Computers
ISBN : 9781098136161

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Software Engineering for Data Scientists by Catherine Nelson Pdf

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success—and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering,and clearly explains how to apply the best practices from software engineering to data science. Examples are provided in Python, drawn from popular packages such as NumPy and pandas. If you want to write better data science code, this guide covers the essential topics that are often missing from introductory data science or coding classes, including how to: Understand data structures and object-oriented programming Clearly and skillfully document your code Package and share your code Integrate data science code with a larger code base Learn how to write APIs Create secure code Apply best practices to common tasks such as testing, error handling, and logging Work more effectively with software engineers Write more efficient, maintainable, and robust code in Python Put your data science projects into production And more

Practical Data Science With Sap

Practical Data Science with SAP by Greg Foss,Paul Modderman Pdf

Practical Data Science with SAP by Greg Foss,Paul Modderman Pdf

Practical Guide to SAP HANA and Big Data Analytics by Dominique Alfermann,Stefan Hartmann Pdf

Practical Data Science by Andreas François Vermeulen Pdf

Practical Data Analysis by Hector Cuesta,Dr. Sampath Kumar Pdf

Data Science for Business by Foster Provost,Tom Fawcett Pdf

Practical Data Analytics for Innovation in Medicine by Gary D. Miner,Linda A. Miner,Scott Burk,Mitchell Goldstein,Robert Nisbet,Nephi Walton,Thomas Hill Pdf

Practical Data Science Cookbook by Prabhanjan Tattar,Tony Ojeda,Sean Patrick Murphy,Benjamin Bengfort,Abhijit Dasgupta Pdf

Practical Data Science with Hadoop and Spark by Ofer Mendelevitch,Casey Stella,Douglas Eadline Pdf

Practical Data Analytics for BFSI by Bharat Sikka,Dr. Priyender Yadav,Dr. Prashant Verma Pdf

SAP Data Intelligence by Dharma Teja Atluri,Devraj Bardhan,Santanu Ghosh,Snehasish Ghosh,Arindom Saha Pdf

A Practical Guide to SAP Data Warehouse Cloud by Klaus-Peter Sauer Pdf

SAP HANA 2.0 by Denys Van Kempen Pdf

SAP Data Services by Bing Chen,James Hanck,Patrick Hanck,Scott Hertel,Allen Lissarrague,Paul Médaille Pdf

Software Engineering for Data Scientists by Catherine Nelson Pdf

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