Trusting increasingly on insight from data to make critical decisions, business frontrunners expect tools to handle data, regardless of source and size, analyze all information and provide quick answers to complex questions. And business users often tend to do it on their own, without depending on IT.

SAS has heard its customers and addressed this problem with its powerful data visualization tool, SAS Visual Analytics. And telecom is one major industry that will benefit from rapid delivery of new SAS capabilities. For example, Telecom Italia tapped SAS Visual Analytics to add in-memory analytics and advanced data visualization to its geo-marketing system, simplifying the decision-support and operational processes for technical and commercial planning. U Mobile has tapped SAS Visual Analytics to enhance informed business decisions, arming executives with visually rich access to real-time consumer behavior. Large mobile operators are actually tailor-fitting services based on customers’ use of data, voice and SMS services.

Our client focused in customer value management and handles telecom data analysis for a large mobile operator (one that has implemented SAS Visual Analytics for better decision making). Solutions include developing single view reporting, descriptive analytics, and predictive analytics. It was interesting to know from Congruent’s data enthusiasts Gopi and Thareek, regarding their experience on our SAS Visual Analytics project:

Tell us more about the client’s data source and type.

The data source is made up of million rows and columns (Oracle) –

  1. Voice call revenue data
  2. SMS revenue data
  3. Data Revenue data

You followed some process to analyze data?

  • Data (Oracle DB converted to SAS data sets) loaded in SAS memory – SAS LASR Analytic Server
  • Explore and analyze data – Drag and Drop functionality. Just pull the required column or row and we can prepare chart in dashboard
  • Possible to load data from different sources like spreadsheets, database, and social media and also from HDFS.
  • Create Reports in a dashboard page of SAS VA tool
  • Customers view reports on their mobile application or through email.

What did you enjoy most about this project? Give us an example.

Data analysis to check any significant growth or decline happened for Net/ SMS/ Call revenue from the past year (data on the users count). If the user count or revenue amount increases/ decreases with respect to the previous year data, then senior zonal heads will work for improvement. They would like to see the data in an easy visual manner, so that they could take the decision faster.

Example: Slab -it can be determined based on the Revenue generation.

  • Low Value Customer: LVC
  • Medium Value Customer: MVC
  • High Value Customer: HVC
  • Ultra High Value Customer: UHVC

 How this analysis helped the operator’s business heads?

Senior heads prepared all different revenue models by analyzing the data manually and finally they represented the analyzed data to their client in pie chart, bar chart and many other graphical representations.

They showed us a Revenue model power point slides which has almost analyzed all the data in visual representation. There were nearly 160 pages of slides. Mostly all the slides were like graph, pie chart, and bar chart representation. Example – SMS revenue details alone were represented in 25 slides. Each and every slide with different analyzed report, like – SMS revenue with access fee, without access fee, on net, off net, revenue in different frequencies [monthly/quarterly/half yearly/annually].

In a nutshell:

On the surface, SAS Visual Analytics is an integrated set of web apps that offers intuitive, drag-and-drop interactions, rapid, highly visual responses, and role-based access to functionality.

  • Administrators prepare data sources and load them to memory.
  • Analysts interactively explore, analyze, and interpret data.
  • Report designers create compelling reports and dashboards.
  • Report consumers view reports on their mobile devices or on the web.

Behind the scenes, SAS LASR Analytic Server handles both big data and smaller sets of data, and processes client requests at extraordinarily high speeds due to the combination of hardware and software that is designed for rapid access to tables in memory. By loading tables into memory for analytic processing, LASR enables analysts to explore data and discover relationships in data at the speed of RAM.

Share with us, what SAS VA can offer best for Telecom subsequently. Congruent will share its experience as we progress in some of the niche analytics projects. Next week we will share some interesting analytics use cases in Telecom. Stay tuned…

 Thank you

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