Analiza danych

Spark. Zaawansowana analiza danych

Uri Laserson, Sandy Ryza, Sean Owen, Josh Wills

Spatial Analytics with ArcGIS. Build powerful insights with spatial analytics

Eric Pimpler

Splunk 7.x Quick Start Guide. Gain business data insights from operational intelligence

James H. Baxter

Splunk Best Practices. Operational intelligent made simpler

Travis Marlette

Splunk Developer's Guide. Learn the A to Z of building excellent Splunk applications with the latest techniques using this comprehensive guide - Second Edition

Kyle Smith

Splunk: Enterprise Operational Intelligence Delivered. Machine data made accessible

Derek Mock, Betsy Page Sigman, Paul R. Johnson, Erickson Delgado, ...

Splunk Operational Intelligence Cookbook. Over 80 recipes for transforming your data into business-critical insights using Splunk - Third Edition

Josh Diakun, Paul R. Johnson, Derek Mock

Splunk Operational Intelligence Cookbook. Transform Big Data into business-critical insights and rethink operational Intelligence with Splunk - Second Edition

Josh Diakun, Derek Mock, Paul R. Johnson

SQL for Data Analytics. Harness the power of SQL to extract insights from data - Third Edition

Jun Shan, Matt Goldwasser, Upom Malik, Benjamin Johnston

SQL for Data Analytics. Perform fast and efficient data analysis with the power of SQL

Upom Malik, Matt Goldwasser, Benjamin Johnston

SQL Server 2017 Administrator's Guide. One stop solution for DBAs to monitor, manage, and maintain enterprise databases

Marek Chmel, Vladimir Muzny

SQL Server 2017 Machine Learning Services with R. Data exploration, modeling, and advanced analytics

Julie Koesmarno, Toma?ae Ka?°trun

SQL Server on Linux. Configuring and administering your SQL Server solution on Linux

Jasmin Azemovifá

Statistical Application Development with R and Python. Develop applications using data processing, statistical models, and CART - Second Edition

Prabhanjan Narayanachar Tattar

Statistics for Data Science. Leverage the power of statistics for Data Analysis, Classification, Regression, Machine Learning, and Neural Networks

James D. Miller

Statistics for Machine Learning. Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R

Pratap Dangeti