Tailored Data Solutions
Overview
Do you have a complex environment?
Are your technology platforms connected?
Do you have bad data?
Everything Data will deliver on your specific business needs, through tailored data solutions.
Our key pillars to successfully fulfill on your objectives are:
- Establish consolidated, clean & usable data
- Unlock invaluable consumer insights
- Deliver exquisite customer experiences
Our experienced team of specialists will work closely with you, through your data journey.
Data Cleansing
Data cleansing is the process of generating clean and usable data.
Our automated processing will improve your data quality through cleansing, enhancement and enrichment.
We will eliminate dirty data, reduce data duplication through automated detection and standardise your data across channels and platforms.
The key is having the right data and getting it fast enough to act, which will dramatically empower your team.
Process
Mapping each of your data sources to automatically cleanse on a periodical basis.
Perform validation, standardisation and correction of attribute details from all your data sources.
Consolidate your datasets to create your single source of truth across channels and platforms.
Produce deeper data-driven insights and analytics to apply segmentation, trends and tribes.
Enable automated personalisation, location intelligence and other in-built features,
Attribute Validation
- Name (title, first, middle, last, company)
- Person role
- Address (physical, postal, non-standard)
- Website
- IP Address
- Telephone (all phone formats including mobile)
- Fixed length identifiers
- Many more, which can be extended to include any client specific attribute validations
Main Challenge
%
Bad Data
Data Transformations
Data transformation is the process of translating one format of data (source) into another format of data (destination).
Typically, this involves data mapping to define how individual fields are: mapped, modified, joined, filtered and aggregated.
In achieving a successful data transformation, the following are some areas, that need to be addressed:
- multiple data sources
- varying data formats
- applied transformation method (mapping rules and logic)
- data duplication
- missing, incorrect or incomplete data
- indexing and defining key identifiers
- default field population rules, to name a few
Data transformations are generally performed in a data warehousing environment, as a pre-cursor to:
- conducting a data migration
- consolidating you data to create a single source of truth (for insights, analytics, reporting and marketing purposes, to name a few)
Examples of use include:
1. introducing a platform to maintain your single source of truth, by automatically processing data from all your core systems.
2. introducing a new CRM system and migrating customer, sales and product data from one or many legacy systems.
3. maintaining an e-commerce platform to refresh your active products with related attribute/price/stock information from your core systems.
High-level data transformation phases are:
Extract
Process of extracting your data source/s into a central repository on a periodical basis.
Transform
Automated process of mapping each data source to perform a clean and transform – ultimately creating a master dataset that produces an output consistent with rules and data structures of the destination format.
Load
Process of loading destination format data, created during the transform phase to ingest into the destination system, as expected and without error.
Challenges
Everything Data provides you with your own feature enabled platform, that is then tailored to your specific needs.
Ultimately, you will leverage from Everything Data’s enabled core capabilities, to deliver your data transformation.
As a result, you can deliver much quicker, than if you attempted to do it from scratch.
Data Migrations
Data migration is the process of selecting, preparing, extracting and transforming data, then permanently transferring it from one storage system to another.
Generally, the system where the data is being transferred from, would be decommissioned after you have completed post-migration activities.
High-level data migration phases are:
Planning
Generally, project based involving project, technical and business resources.
- Feasibility
- Hardware
- Architecture
- Licensing
- Scripting (ETL development to perform cleansing and transformation through mapping, processing of business rules to produce quality data – eliminating redundant/obsolete information)
- Change Management
Migration
- Hardware/software validated and procured
- Backup your data
- Pre-validation testing
- Data extraction
- Data loading
Post-Migration
- Data verification, which may require a parallel run of both systems
- Business support processes in place
- Operational training
- Post-migration documentation (reports, summaries)
- Migration close-out meeting, which determines the official completion of the data migration process
Obviously, the above summary does not constitute the full array of activities, however it does indicate the complexity and involvements required for a data migration.
Our team of experienced specialists at Everything Data, will ensure you deliver a successful data migration.
Data Integrations
Data integration is the process of establishing and maintaining a single source of truth, combining data residing in different sources and providing users with a unified view.
Typically, this is performed within a data warehousing environment that performs ETL (extract, transform, load) processing on a periodical basis from the in-scope data source/s.
Expert data custodianship will deliver your single source of truth.
Fundamentally, having transformed data will:
- unlock invaluable consumer insight
- empower your team
- increase customer acquisition, customer retention and revenue through improved data capabilities
Challenges
Benefits
Secure & Integrated
Access to your single source of truth from our central repository
Data Accuracy & Reliability
Consolidated, clean and usable
Business Intelligence
Improved data capabilities
Data-Driven Strategic Insights
Segmentation, trends and tribes
Predictive analytics identifying patterns, behaviours and interests
Increased Customer Acquisition & Retention
Maximise customer satisfaction, customer loyalty and revenue
Personalised customer journeys
Tailored interactions – right place, right time, right message
Track and analyse customer satisfaction
Everything Data provides you with your own feature enabled platform, that is then tailored to your specific needs.
Master Data Management
Master data management (MDM) is the method used to manage the critical data of an organisation, establishing a single point of reference to govern this activity.
The objective is to always have data that is consistent, accurate and controlled, which will support business function and decision making.
The processes which support this objective, is to ensure data is collected, aggregated, matched, consolidated, quality-assured, persistent and distributed for business use.
Identification of any root cause problems, with remediation (either technical or operational) being facilitated by the MDM group.
Everything Data can support you with your specific MDM needs.