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Best data management foundations of data analytics
1. Data Management: Databases and Organizations
Description
Data Management 6th Edition provides broad coverage of the design and maintenance of computer-based organizational memory. Starting with a managerial perspective, it then takes a deep dive into data modeling and SQL, and then covers advanced data management and the management of organizational data stores. The sixth edition includes new chapters on R, data visualization, text mining, clustering computing, and dashboards. The latest version is dated July 17, 2017.2. Foundations of Data Science: A Practical Introduction to Data Science with Python (Addison-wesley Data & Analytics Series)
Description
Data science underlies Amazon's product recommender, LinkedIn's People You Know feature, Pandora's personalized radio stations, Stripe's fraud detectors, and the incredible insights arising from the world's increasingly ubiquitous sensors. In the future, the world's most interesting and impactful problems will be solved with data science. But right now, there's a shortage of data scientists in every industry, traditional schools can't teach students fast enough, and much of the knowledge data scientists need remains trapped in large tech companies.
This comprehensive, practical tutorial is the solution. Drawing on his experience building Zipfian Academy's immersive 12-week data science training program, Jonathan Dinu brings together all you need to teach yourself data science, and successfully enter the profession.
First, Dinu helps you internalize the data science "mindset": that virtually anything can be quantified, and once you have data, you can harvest amazing insights through statistical analysis and machine learning. He illuminates data science as it really is: a holistic, interdisciplinary process that encompasses the collection, processing, and communication of data: all that data scientists do, say, and believe.
With this foundation in place, he teaches core data science skills through hands-on Python and SQL-based exercises integrated with a full book-length case study. Step by step, you'll learn how to leverage algorithmic thinking and the power of code, gain intuition about the power and limitations of current machine learning methods, and effectively apply them to real business problems. You'll walk through:
- Building basic and advanced models
- Performing exploratory data analysis
- Using data analysis to acquire and retain users or customers
- Making predictions with regression
- Using machine learning techniques
- Working with unsupervised learning and NLP
- Communicating with data
- Performing social network analyses
- Working with data at scale
- Getting started with Hadoop, Spark and other advanced tools
- Recognizing where common approaches break down, and how to overcome real world constraints
- Taking your next steps in your study and career
Well-crafted appendices provide reference material on everything from the basics of Python and SQL to the essentials of probability, statistics, and linear algebra -- even preparing for your data science job interview!
3. Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
Description
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?
In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.
- Peer under the hood of the systems you already use, and learn how to use and operate them more effectively
- Make informed decisions by identifying the strengths and weaknesses of different tools
- Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity
- Understand the distributed systems research upon which modern databases are built
- Peek behind the scenes of major online services, and learn from their architectures
4. Hadoop: The Definitive Guide: Storage and Analysis at Internet Scale
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O Reilly MediaDescription
Get ready to unlock the power of your data. With the fourth edition of this comprehensive guide, youll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters.
Using Hadoop 2 exclusively, author Tom White presents new chapters on YARN and several Hadoop-related projects such as Parquet, Flume, Crunch, and Spark. Youll learn about recent changes to Hadoop, and explore new case studies on Hadoops role in healthcare systems and genomics data processing.
- Learn fundamental components such as MapReduce, HDFS, and YARN
- Explore MapReduce in depth, including steps for developing applications with it
- Set up and maintain a Hadoop cluster running HDFS and MapReduce on YARN
- Learn two data formats: Avro for data serialization and Parquet for nested data
- Use data ingestion tools such as Flume (for streaming data) and Sqoop (for bulk data transfer)
- Understand how high-level data processing tools like Pig, Hive, Crunch, and Spark work with Hadoop
- Learn the HBase distributed database and the ZooKeeper distributed configuration service
5. Data Management: Databases & Organizations
Description
Wanted: Expert Data Modeling and SQL Skills... Inquire Within.Data modeling and SQL--these are the data management skills that are in demand in today's job market. That's why Richard Watson's Fifth Edition of Data Management: Databases and Organizations offers in-depth, fully integrated coverage of data modeling and SQL, and a broad managerial perspective.
Updated with the latest developments in the field, the Fifth Edition will help you design and create relational databases, formulate complex SQL queries, understand OLAP, use SQL with Java, learn how to use XML, and prepare yourself for the real world of data management.
New Features of the Fifth Edition:
* A new chapter on embedded SQL in Java and JDBC
* A section on multidimensional expressions (MDX)
* New material on content management systems (CMS) and wiki technology
* Greater focus on MySQL
* Increased coverage of mandatory and optional elements in data modeling
6. Fundraising Analytics: Using Data to Guide Strategy