Tips for Leveraging SAP Data Services 4.2 by Incorporating Geographical Information to Enrich Your Data

  • by Anurag Barua, Principal, TruQua Enterprises
  • May 23, 2017
One of the most under-used areas of SAP Data Services is its capability to not only add a comprehensive geographical dimension to your data, but also ensure that such enhanced data is of the highest quality. Data Services provides multiple transforms that make this happen. A transform, such as a geocoder, allows you to derive latitude and longitude based on address data, or vice versa. Address cleansing transforms help ensure that the address data that flows in is accurate.
Learning Objectives

Reading this article, you will learn:

  • The various functions (transforms) that are available to achieve geocoding and cleansing
  • The key concepts behind geospatial analysis
  • How to use SAP Data Services to geocode and cleanse this geocoded data
Key Concept
SAP Data Services enriches any address data entering your application by incorporating value-added geographical components, while ensuring that this data is clean and accurate. This clean geocoded data can then be used by a Business Intelligence application to do geospatial analysis.

How often have you stared at a sales report or a dashboard with all the metrics and key performance indicators (KPIs) and wondered how much more convenient it would be to have all these metrics displayed on a map? Or stared at a supply chain report or dashboard thinking how much easier it would be to visualize all the information about where the delivery trucks are and how many there are on a map?

I can certainly say from my own experience that the answer to both these questions is likely to be many times. Indeed, geospatial analysis is a powerful paradigm that enables you to visually answer the where question; compute the shape and size of data clusters (such as suppliers and vendors) and the distribution of business entities, such as plant locations and warehouses; discover relationships amongst objects on the map; optimize distances; detect patterns; and perform prescriptive and predictive analytics.

The key to geospatial analysis is to successfully geocode your data (that may not have all or any of the geographical components such as addresses, postal and ZIP Codes, latitudes, and longitudes). Generally, data entering transactional systems such as SAP ERP and SAP ERP Central Component (ECC) does not have all the geographical components and therefore geocoding is necessary to enable complete, accurate, and effective geospatial analysis.

Key Terminology

Here are some key terms that are relevant to this article that you need to understand.

  • Geographic information system (GIS) – GIS is a software application that enables users to acquire, manage, present, and visualize geographical data on a map to recognize and analyze trends and patterns, and thus make effective decisions.
  • Geocoding –Geocoding is the process of adding geographical coordinates, namely latitude and longitude, and other related geographical attributes to address data. You can also call this address geocoding.
  • Reverse geocoding – As the name suggests, in this process, the data containing geographical attributes such as the coordinates is deconstructed into an address (at the highest level of granularity) or less specific information such as a point of interest, landmark, region, or county.
  • Spatial intelligence – Everyone is familiar with the term business intelligence (BI). The geographical components, when added to a BI system, gives it another space dimension. Additionally, many GIS packages provide tools and software development kits (SDKs) to design custom geographical functionality. All of this provides you with the ability to analyze your data from the space dimension.

Address Data and Data Quality

Data quality is of the utmost importance when you are dealing with address data. By now, you might have inferred that the success of spatial intelligence lies in accurate geocoding. This success is only possible if the data entering your system is of sufficiently high quality. There is probably not a single global organization that does not have to grapple with incomplete or incorrect customer or vendor/supplier address data. Such data needs to be either cleaned or completed to avoid downstream impacts such as incorrect reporting and erroneous decision-making.

Anurag Barua

Anurag Barua is a principal at TruQua Enterprises. He has 23 years of experience in conceiving, designing, managing, and implementing complex software solutions, including nearly 18 years of experience with SAP applications. He has been associated with several SAP implementations in various capacities. His core SAP competencies include FI and Controlling (FI/CO), logistics, SAP HANA, SAP BW, SAP BusinessObjects, Enterprise Performance Management, SAP Solution Manager, Governance, Risk, and Compliance (GRC), and project management. He is a frequent speaker at SAPinsider conferences and contributes to several publications. He holds a BS in computer science and an MBA in finance. He is a PMI-certified PMP, a Certified Scrum Master (CSM), and is ITIL V3F certified.

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