Updated: Feb 14
BUSINESS CASE #1: THE DATA MIGRATION PROJECT
Background: Enterprise application implementations can be challenged at the point of data migration. These projects include CRM, ERP, SCM, DW, Marketing platforms. Switching or launching systems is a perfect time to re-evaluate data quality and information standardization. It’s also a great time to consider the level of outside professional assistance you might need. Let’s face it, your team is better tuned to development, integration and application administration. You may have project managers and architects, but data migration is a different ball game. Way too many migrations suffer from putting old, unreliable data into new enterprise applications. And the cleansing effort is often under-estimated and forced into an Agile time box.
Admonishment: Don’t put old, invalid data into a new system. Data is perishable and keeping it fresh is a constant challenge. Every business has old, inaccurate, incomplete data sets that cause uncertainty and doubt about how to raise profitable revenue. Part of the problem with your last application solution was data, and the bad data resulted from some of the solution inadequacies. You have made database changes over time.
Your choices? Just walk away and start fresh. Sure, but that does not give you any wisdom from the accumulated efforts of customer interaction over the years. Keep the bad data? That won’t give confidence to the users and execs who just paid for the new system.
Door number 3. When you move to a new business application, you should clean and revitalize your customer-related information and restore it to a trusted, actionable state. Let us use our tools to help your team's launch succeed on “day 1”. Our high-performance data science technologies will take you from weeks and months to days and hours.
But the task can be a bit of a quagmire…unless you are experienced and have the proper tools. At Ascendant Group, we can quickly and cost-effectively rationalize your data sets for transport from one set of applications to another, and assure this data is right with the world.
Don’t just move bad data around. Fix it; enrich it; make it reliable. Let us help make you a data all-star!
Problems we solve:
Fields in different tables or databases need consolidation and standardization
Fields contain invalid characters or entries
Missing common data model for customer-centric attributes
Correlated fields with orthogonal data sets
Missing data in important fields
Duplicate but misaligned fields across tables and databases
Duplicate records to a real-world identifiable object (contact, account, address, transaction)
Reliable, sophisticated “fuzzy” matching of duplicates
Spelling, punctuation, character use
Data missing sense of master UID’s
Accounts missing important hierarchical relationships
Transactions missing important attribution to predecessor causes
Cannot map transactional and activity data across databased because of missing master data UID’s
Too many tables deep: you need to keep the data but not the table. We can easily deformalize to meet the needs of your new ERD.
Making fields into records. Perhaps you need to normalize and articulate companion fields that should be child records of the new schema
Missing was to track unique instances of parental data in N-N transactional records between parent records
Rule-based, smart null data backfilling
Invalid address, phone, email, social accounts, web sites, IP trackers; disconnected
Old or non-sanctioned terminology used in text fields; need powerful search and replace
Inactive record detection and classification with cascading to child records
Diverse file transformation and ingestion with universal formatting
PII not classified for compliance
Unable to lock and anonymize data for GDPR and CCCP compliance. Do Not Call opt out management
Data change traceability and control totals
Total Accessible Market: use your customer and prospect records to find every other target in the known marketplace using our list services. Get new accounts and contacts for those accounts
Intelligent field split, concatenate, shift, metadata counts, character removal
Deceased, out of business and moved-no forward
Address element correction, validation
Address occupancy validation, move update, PO Box & street address rationalization
No objective standards for demographic, firmographic and geographic information sets
Missing marketplace attributes from trusted 3rd party sources: demographics, firmographics, geographics, license, property, auto public records
Social URL appends
Metrics calculations and summarizations