Self Service Analytics & its Components

Need for Self Service analytics 

In current competitive market the companies who will win will be the companies who can harness its full potential of data. To easily access the data, it needs to be integrated, tagged, quality assured and made easily available for relevant business users so that they can create the metrics for their business themselves.

 Self-Service Analytics (SSA) is an ecosystem of tools to present company’s enterprise data to its users in an easy to find, easy to consume and easy to analyses manner like we can find the product in an eCommerce marketplace and order not only the needed product but also the other related products which makes consumer experience delightful.

To do its job, companies need to ensure that the people using the tool can easily access the data they need across the organization – including siloed data living in various systems – and have full confidence in this data to apply it for greater business insight and results.

Key Components / Tools to facilitate Self-Service Analytics (SSA) solution

Please fine above Self-Service Analytics (SSA) - Example Architecture Diagram.

Below I am providing a very brief summary of required Components / Tools to facilitate Self-Service Analytics (SSA).

 A.  An Enterprise Data warehouse & A Data Lake

 1. Defined process around Data Governance which will cover Data Security, Data access rules, etc

 2. Pre calculate Industry standard pre-defined KPIs can be prebuilt and related document needs to be published.

3. Integrate 3rd party data like Weather data, Macro Economic data, etc for power users.

 4. Integrate other data like factory data, machine sensor data, etc

B.  Enterprise ETL Tool

Modern Extract Transform and Load (ETL) Tools like Informatica, Alteryx, Tableau Prep, SAP BODS, etc. is a must have to build a modern Data warehouse and Data lake.

Below is a snapshot from Tableau Prep:

In addition to ETL tool additional specialized connectors may be needed to connect to some data sources like SAP, ERP, etc.

For example, leading Connectors to connect to SAP data source are VirtDB, Theobald Extract Universal, DVW Analytics, etc.

C.  Data Catalog

We need to publish Enterprise Data Catalog and Data linage of the overall Enterprise data.

Optionally we may need Data Model and Meta Data management tool if Data catalog is not supporting the same.

This will help in to produce a well-documented Data Models for normalized (OLTP-3NF) as well as de-normalized (Datawarehouse - Dimensional) Data Models as per the need.

Published data model with subject area wise will help end user to know what is available and this will also help in self-service analytics

End user Document and training for the use of Self-service framework (Data Model, tools,)

D.  Self-Service Analytics Data Visualization Tools

Easy to use and visually appealing Dash-boarding and Reporting tool is the most critical tool of any Self Service analytics framework as this is the front end for the end user who will consume the final product in the form of Dashboard and reports.

 Below are some of the mainstream Self service Data visualization tools which is a must have components for SSA. Please select one according your Analytics need. 

        I.       Tableau

        II.       SAP Analytics Cloud SAC

        III.       SAP BO

IV Power BI

Conclusion  

One drawback of Self-Service analytics is that it requires standardization of the tools and analytics platform for all the users. Everybody can not use all sort of tools according to their choice, but has to select one most appropriate tool according to enterprise need.

This helps in collaboration between IT and business around requirements and development and hence necessary for speed of delivery.

Considering all, in today’s competitive world, SSA is a must have for any big enterprise due to wide verity of data and systems it possesses. Elephant has to dance to be able to compete with all companies whether small or big. 

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