deck.gl: Visualizing Large-scale Geospatial Data Training Course

This instructor-led, live training in Peru (online or onsite) is aimed at field ecologists and conservation managers who wish to create data spatial projects in ArcGIS.

By the end of this training, participants will be able to:

• Output spatial data as visualizations.
• Conduct geostatics on actual data.
• Implement spatial data analysis, data processing, and mapping with ArcGIS.
• Analyze spatial data for projects in ArcGIS.

This instructor-led, live training in Peru (online or onsite) is aimed at intermediate-level environmental scientists and archaeologists who wish to learn how to use ArcMap in ArcGIS for collecting, organizing, managing, and analyzing geographic information.

By the end of this training, participants will be able to:

• Understand the fundamentals of ArcMap and ArcGIS.
• Collect, organize, manage, and analyze geographic information on the social and archaeological elements.
• Conduct spatial queries for impact evaluation.

By the end of this training, participants will be able to:

• Understanding GIS concepts and spatial data types using the latest version of ArcGIS Pro.
• Investigate the user interface and evaluate the uses
• Explore ArcGIS* Pro and how to utilize online content
• Manage, manipulate and analyze your own data
• Display and share your data in a meaningful and creative way

Note: We will use the latest version of ArcGIS Pro.

This instructor-led, live training in Peru (online or onsite) is aimed at GIS analysts who wish to automate repetitive tasks in GIS processes.

By the end of this training, participants will be able to:

• Build GIS applications using Python and ArcGIS tools.
• Develop with the ArcGIS package ArcPy, using Python.
• Apply the ArcGIS modules for map automation using object classes in Python.

A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data. The acronym GIS is sometimes used for geographic information science (GIScience) to refer to the academic discipline that studies geographic information systems and is a large domain within the broader academic discipline of geoinformatics.

QGIS functions as geographic information system (GIS) software, allowing users to analyze and edit spatial information, in addition to composing and exporting graphical maps. QGIS supports both raster and vector layers; vector data is stored as either point, line, or polygon features. Multiple formats of raster images are supported, and the software can georeference images. To summarize it allows the users to Create, edit, visualise, analyse and publish geospatial information on Windows, Mac, Linux, BSD.

This program, in its first phase, introduces the QGIS interface for general usage. In the second phase, we introduce PyQGIS - the python libraries of QGIS that allows the integration of GIS functionalities in your python code or your python application, so that you may even create your own Python Plugin around a particular GIS functionality.

This instructor-led, live training in Peru (online or onsite) is aimed at field ecologists and conservation managers who wish to post-process Pix4D drone data.

By the end of this training, participants will be able to:

• Implement Google Earth to enhance UAV mapping .
• Use outputs of images to generate reports.
• Post-process with GIS and CAD software for advanced drone data modeling.

This instructor-led, live training in Peru (online or onsite) is aimed at field ecologists and conservation managers who wish to land survey and drone map with Pix4D.

By the end of this training, participants will be able to:

• Use end to end drone mapping processes and techniques.
• Achieve high surveying accuracy.
• Understand the fundamentals of global coordinate systems and GPS.
• Generate and analyze survey output with Pix4D's image processing software.

This instructor-led, live training in Peru (online or onsite) is aimed at intermediate-level geographers who wish to deepen their expertise in spatial analysis, data management, and GIS applications.

By the end of this training, participants will be able to:

• Apply advanced spatial analysis techniques to solve complex geographical problems.
• Manage large spatial databases and perform data quality control.
• Create dynamic and interactive maps and visualizations for various applications.
• Utilize programming and automation to streamline GIS workflows.

This instructor-led, live training in Peru (online or onsite) is aimed at developers who wish to enhance their website or web application by adding geo-location functionality through Google Maps.

By the end of this training, participants will be able to:

• Embed a map into a new or existing website or web application.
• Display live data that synchs with current location.
• Create a mashup that includes Google Maps.
• Apply good CSS and JavaScript coding practices
• Create a custom map for an application.

A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data. The acronym GIS is sometimes used for geographic information science (GIScience) to refer to the academic discipline that studies geographic information systems and is a large domain within the broader academic discipline of geoinformatics.

The use of Python with GIS has substantially increased over the last two decades, particularly with the introduction of Python 2.0 series in 2000, which included many new programming features that made the language much easier to deploy. Since that time, Python has not only been utilized within commercial GIS such as products by Esri but also open source platforms, including as part of QGIS and GRASS. In fact, Python today is by far the most widely used language by GIS users and programmers.

This program covers the usage of Python and its advance libraries like geopandas, pysal, bokeh and osmnx to implement your own GIS features. The program also covers introductory modules around ArcGIS API, and QGIS toolboox.

Magellan is an open-source distributed execution engine for geospatial analytics on big data. Implemented on top of Apache Spark, it extends Spark SQL and provides a relational abstraction for geospatial analytics.

This instructor-led, live training introduces the concepts and approaches for implementing geospacial analytics and walks participants through the creation of a predictive analysis application using Magellan on Spark.

By the end of this training, participants will be able to:

• Efficiently query, parse and join geospatial datasets at scale
• Implement geospatial data in business intelligence and predictive analytics applications
• Use spatial context to extend the capabilities of mobile devices, sensors, logs, and wearables

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Peru (online or onsite) is aimed at intermediate-level database administrators, SQL developers, and data analysts who wish to enhance their SQL skills by mastering the use of Analytic Functions.

By the end of this training, participants will be able to:

• Understand the concept and importance of Analytic Functions.
• Apply various Analytic Functions to solve complex analytical problems.
• Combine Analytic Functions with other SQL features for comprehensive data analysis.
• Optimize queries for better performance using Analytic Functions.

Apache Arrow is an open-source in-memory data processing framework. It is often used together with other data science tools for accessing disparate data stores for analysis. It integrates well with other technologies such as GPU databases, machine learning libraries and tools, execution engines, and data visualization frameworks.

In this onsite instructor-led, live training, participants will learn how to integrate Apache Arrow with various Data Science frameworks to access data from disparate data sources.

By the end of this training, participants will be able to:

• Install and configure Apache Arrow in a distributed clustered environment
• Use Apache Arrow to access data from disparate data sources
• Use Apache Arrow to bypass the need for constructing and maintaining complex ETL pipelines
• Analyze data across disparate data sources without having to consolidate it into a centralized repository

Audience

• Data scientists
• Data engineers

Format of the Course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Peru (online or onsite) is aimed at data engineers and analysts who wish to learn beginner to intermediate-level knowledge of using AWS Glue to set up a data pipeline.

By the end of this training, participants will be able to:

• Understand the fundamentals of AWS Glue.
• Set up an AWS Glue pipeline.
• Set up AWS Glue crawlers and jobs.
• Learn how to use AWS Glue transformations.

Data analysis refers to the process of obtaining, cleaning, and analyzing data, often times in a visual manner, to derive insights for better decision making. More and more data is being stored in databases in the cloud so it is important to have a strategy for understanding, managing and accessing such data. One popular tool for accessing and visualizing data is Power Bi.

This instructor-led, live training (online or onsite) is aimed at technical persons who wish to gain a practical understanding of available cloud solutions, the data analysis processes needed to work with data in the cloud, and the hands-on practice to apply tools such as Power BI to analyze data.

By the end of this training, participants will be able to:

• Install and configure Power BI.
• Evaluate the various data solutions offered by cloud providers such as Azure.
• Gain an understanding of the different structures, modeling approaches, and data warehouse designs used to store, manage and access Big Data.
• Apply tools and techniques to clean data in preparation for analysis.
• Build reporting and analytics solutions based on on-premise as well as cloud data.
• Integrate data analytics solutions with a data warehouse.
• Mitigate data security risks and ensure data privacy.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.