2021-08-31T19:56:00Z
MH
Customer Insights Manager at rackroom
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How to build a Customer 360 view?

Hi community,

I work as the Customer Insights Manager at a Retailer company with 1000+ employees.

I'm just starting to implement a Customer 360 view but I have customer data spread across multiple data platforms.  

What elements should I include and which I shouldn't? Please advise.

I'm trying to keep it as simple as possible without having to go back later and re-invent or add.  

3
PeerSpot user
3 Answers
MW
Enterprise MDM Architect / Solution Arch at a energy/utilities company with 10,001+ employees
Real User
Top 5Leaderboard
2021-09-12T19:21:09Z
Sep 12, 2021

Hi @Mark Hunt,


A problem statement that you have provided is very common while building the consolidated Customer data view.


All projects start with the requirements. In the case of Customer 360 initiatives, the requirements should cover at least the following aspects:


- Logical data model of the customer domain


- Identification of all entry points of the customer data


- Assessment of which pattern your MDM system will follow


- Identification of the data owner of the customer data domain and all other key stakeholders: process owner, data architect, data stewards and many others (depending on the size of your company)


- Physical models of all systems that will be used to integrate customer data into your Customer hub and all systems which may consume customer data. Ideally, you should think of exposing the data via generic APIs, so that later you can add additional downstream systems with little effort.


- Collect all policies, procedures, standards (including cleansing, enrichment, standardization, etc) to govern customer master data


- Collect all match & merge rules to build the golden records of the customer data while integrating the data from multiple sources.


I am sure there's much more. Just ask if you need further details.

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EB
Director of Community at PeerSpot (formerly IT Central Station)
Community Manager
2021-09-11T04:41:27Z
Sep 11, 2021

Hi @AnilKumar21, @InitZero, @Monirul Islam, @Jaime A. Rendón ​and @Harisha Acharya,


Can you please chime in here and share your knowledge with the community? Thanks.

DA
CEO at a tech services company with 51-200 employees
Real User
Top 10
2021-09-06T13:35:26Z
Sep 6, 2021

Hi Mark, 


I wish you're well and safe. 


Before you start, you should use a very good data prep tool. 


For that, in terms of elements, you should analyze 2 things: (1) which elements are common for all platforms and (2) which elements the business requires as mandatory; from this point, you will be ready to prepare a good model to move forwards. 


Later, you can add more attributes for advanced analytics, but start with mandatory elements. 


Good luck!

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Hi Jon, I can help out. We at best can use a conference call to discuss this if you agree. My contact details are: - info@nero-advies.nl; - +31 6 28 570 870 I am lcoated in the Netherlands and the CET timezone. I have over 5 years'of experience and knowledge in detail on iPaaS, API Management, API Gateways and ESBs and are currently advising and implementing it at top 5 global brands and local Dutch market leaders. Cheers, Markus.
it_user660567 - PeerSpot reviewer
Business Development at Talend
Apr 4, 2018
Talend platform can help with this. since integration is key in this aspect, you need to be able to a) connect with ease and without limitation and b) scale your platform as the requirements grows without being limited by costs and excessive systems requirements, and finally C) improving productivity through the reuse of what you've already created. Talend offers a modular approach to their platform, you scale this depending on your requirement so you only pay for what you need. The modules available are form open source to enterprise Data integration, data quality, ESB, MDM, real time big data, metadata manager, API manager RESTLET, self service applications: Data preparation and data stewardship. connectivity is a major point since 900+ connectors are available out of the box and more are available from the open source community, alongside API and JDBC type approach. ease of use: Visual UI that uses a drag and drop approach, Source systems on the left, target systems on the right- from there you practically draw your integration job. Talend admin Console: a single console to govern all talend modules, allows for scheduling, automation, access to shared repository, monitoring and managing deployments etc. developer cooperations, code reusability, impact analysis, governance rules, etc Code Reusability: Talend offers a native code generator, where development can start off in (eg. Java and when required can later be generated in Spark, Mapreduce, or storm or any other code. this element is also available with regards to the repository since you can access code already created( as long as governance rules permit) commercial factor: talend price is based on the number of talend developers: so in your case, you'll only need to think about one or two developer licenses. in fact with less than 25k , you can have an annual subscription of a hybrid talend cloud integration platform, giving access to Data Integration, Data quality, Bigdata with multiple remote and cloud engines included. There is no charge for the amount of data you use, and all connectors and support is out of the box. Infact, if you wanted, you can actually start integrating your systems using the open source tool: Talend Open studio for data integration and when you're ready, you can upgrade and migrate to enterprise without losing any of the work you've done on the open source tool.
Ariel Lindenfeld - PeerSpot reviewer
Director of Community at PeerSpot
Aug 2, 2017
Let the community know what you think. Share your opinions now!
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it_user713637 - PeerSpot reviewer
Sr Director, Strategic Business Development at Informatica
Aug 2, 2017
Understand current and future use case requirements. Data has SLAs. You don't want to make credit risk decisions on batch file data that was transferred in last Friday. Latency in cloud based data delivery may be a problem. it's called making sure the data is "fit for purpose". Also, the ability of your integration tools to generate metadata that can be consumed externally, for example by a data catalog, is very helpful. Finally, what is the architecture for including data quality, DaaS, enrichment services, exposing web services, etc.? Think big, start small, grow fast.
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