What is Alteryx ?
Alteryx is a leader in analytic process automation. Alteryx empowers BI analysts with a re-useable workflow for self-service data prep, so you can spend less time preparing data and invest more time analyzing data. It works with multiple data sources and performs complex analytics including Predictive, statistical, and spatial analysis.
Alteryx is an ETL tool so it is used for data preparation, which is the process of converting your raw data into clean usable data which can be used for analysis purposes. To understand ETL let's understand the aspect of this process:
Extract(Retrieve): Extraction is the process of fetching data from different data sources where your input resides, and input it in the Alteryx framework.
Transform: Transformation is the process of cleaning your data. Data cleaning includes a check for missing data, duplicate data, removal of special characters, spaces, null values.
Load: After Transformation your data is ready for analysis, so you can export the output from Alteryx into multiple formats.
For data preparation, these three are the main components and for performing these 3 components we will use different categories of tools into Alteryx.
Alteryx framework consists of 4 products.
Alteryx Designer: It is a windows software application that provides an intuitive drag-and- drop user interface for users to create repeatable workflow processes. Users can drag tools from a toolbox onto a canvas, connect them together, and edit their properties to create Alteryx workflows, apps, and macros.
Alteryx Server: Alteryx server is used for Sharing workflow, Analytics App and to schedule workflows.
Alteryx Connect: It helps locate assets that can be used for data preparation. It provide a catalogue and metadata of all the assets. Alteryx connect will make any of your corporate data just few clicks away from anyone, it will connect people around data and it will be the place to capture your corporate data knowledge
Alteryx Promote: It helps deploy, manage, and monitor predictive and machine learning models in production. That is enabled by embedding Alteryx, R, and python models in production applications and referencing them through APIs.