software/data_analytics.md: first content draft

doc.zih.tu-dresden.de/docs/software/data_analytics.md

+On the ZIH system, there are many possibilities for working with tools from the field of data analytics.
+The boundaries between data analytics and machine learning are fluid. 
+Therefore, it may be worthwhile to search for a specific issue within the data analytics and machine learning sections.
+
+The following tools are available in the ZIH system, among others:
+
+1. [Python](data_analytics_with_python.md)
+1. [R](data_analytics_with_r.md)
+1. [Rstudio](data_analytics_with_rstudio.md)
+1. [Big Data framework Spark](big_data_frameworks_spark.md)
+1. [TensorFlow](tensorflow.md)
+1. [Pytorch](pytorch.md)
+
+Additional software or special versions of individual modules can be installed individually by each user.
+If possible, the use of virtual environments is recommended (e.g. for Python). 
+Likewise software can be used within [containers](containers.md). 
+
+For the transfer of larger amounts of data into and within the system, the [export nodes and data mover](../data_transfer/overview.md) should be used.
+The data storage takes place in the [work spaces](../data_lifecycle/workspaces.md). 
+Software modules or virtual environments can also be installed in workspaces to enable collaborative work even within larger groups. 
+General recommendations for setting up workflows can be found in the [experiments](../data_lifecycle/experiments.md) section.