Unlock the power of storytelling!

This page equips you with engaging booth stories that highlight our key messaging points.

Key Messaging

Core capabilities & booth experts

Data Enrichment

Antonio, David, Colin

Data Governance

Antonio, Sue, David

Data Integration

Evolve/EW: Andrew, Tammy, Jayasri
Data Integrity Suite: Antonio

Data Quality & Observability

Antonio, Sue, David

Data Security & Privacy

Sue, Antonio, Shalaish

Geo Addressing & Spatial Analytics

Antonio, Colin, David

Master Data Management

High Level: Andrew, Tammy, Sue, David
Technical: Jayasri

Process Automation

Andrew, Tammy, Jayasri

Key Messaging

  • Precisely, the leader in data integrity
  • Accuracy, Consistency, Context
  • Unique blend of software, data, and strategic services

Data Integrity for:

Artificial Intelligence

  • Idea: Garbage in, garbage out. Data Integrity is step 0 for any AI initiative.
  • Question: What data is feeding your AI initiatives and is your data AI ready?

Analytics and BI

  • Idea: If your data isn’t fit for purpose and automated then you’re falling at the first hurdle in regard to analytics and BI
  • Question: What data is driving your analytics insights? Do you trust this and how do you ensure data quality?

Mainframe Modernization

  • Idea: Manual and siloed data across the organisation creates inefficiencies in downstream processes.
  • Question: Where are you on your cloud modernization journey (everyone is on one)? How are you incorporating legacy systems into this?

Compliance

  • Idea: Lack of infrastructure, process and reporting creates compliance blind spots.
  • Question: How do you prove compliance and what challenges do you face in delivering that proof?

Horizontal Discovery Questions

  • What is your core data strategy and where are you within this now?
  • Where are some of the opportunities you see for development/improvement within this strategy?
  • What tools & systems are you currently using to support this strategy?
  • Is your data strategy business or IT driven?
  • How reliant is your business/team on SMEs.

Start the Story

Data Integrity means you have truly useful, trusted data that you can rely on to support critical business decisions and activities …

Data Enrichment

Continue the Story

… Achieving data integrity means you can centrally manage master data across all your systems and enrich and enhance that data for even greater insights and value, unlocking the true potential of your data.

Customer Challenges

  • Accessing, integrating, cleansing, and enriching data requires a highly skilled SME or external resource.
  • Data is difficult to find or access.

Differentiators

  • Data enrichment capabilities with over 400 curated data sets that allow us to expand with your business.
  • Expansive global data sets meaning less time prepping data and more time meeting business goals.
  • Easy enrichment of addresses with valuable context using a PreciselyID.

Customer Stories

Keller Williams

KW App leverages extensive curated content directly from internal systems while also supporting direct communications and interactive decision making with their agent.

International Streaming Service – Disney/Hulu

Roll out a “Unified Platform” leveraging location data to grow revenue opportunities

Leading Fast Food & Beverage organizations – Starbucks, McDonalds

Roll out a “Unified Platform” leveraging location data to grow revenue opportunities

  • Gain clarity on spending and behavior
  • Captured 8% increase by understanding history of purchasing
Largest Social Media Apps – Meta/Twitter

Leverage essential data such as boundaries for location quality and verification when interacting such as ‘checking in’

Capability Specific Discovery Questions

  • What does your data vendor landscape look like? Are you working with multiple suppliers across the business/departments?
  • How does data enable your understanding of the risks and opportunities associated with different locations?
  • What is your current exposure to static and/or dynamic data in your decision making?

Data Governance

Continue the Story

… The data integrity journey continues with integrated data governance and continuous quality checks and improvements for all data types and sources. Allowing you to find, understand and trust your data.

Customer Challenges

  • Data asset ownership, content, lineage, and meaning are unclear causing inaccurate and inconsistent business outcomes.
  • Visibility into data quality scores, rules, and metrics to drive confident, trusted data-driven decisions.
  • Do not know what data assets exist causing wasted operational expense looking for it. (catalog)
  • Data assets are not available or understood causing missed business opportunities.

Differentiators

  • Business-friendly features (flexible metamodel, 3D diagrams, and workflow) to increase ROI & adoption by business & IT teams
  • Embedded tracking and metrics linked to goals and KPI’s to bring visibility to real business value.
  • High scale, highly performant data catalog future-proofs your investment for high volume, complex environments

Customer Stories

Northwest Bank
Trusted data for compliance & revenue generation
International Streaming Service – Disney/Hulu

Roll out a “Unified Platform” leveraging location data to grow revenue opportunities

Central Mutual

Improve confidence in data as an asset strategy

Ascensus

Strategy to develop single place to access data

Capability Specific Discovery Questions

  • What are your goals for data governance? Are you looking more to increase data literacy or data discovery?
  • How would you describe the data literacy of your organization?
  • What strategies to you have in place to inventory your data assets?
  • How do you bring visibility around data quality processes, rules, and metrics to data users?
  • What kinds of challenges have you seen with getting data governance programs started? IT/business resources?
  • What metrics do you have in place to prove your data governance initiative is delivering ROI and meeting objectives?

Data Integration

Continue the Story

… Having trusted data often starts with having near real-time access to all your data from across the business. Data Integration at Precisely enables organizations to quickly build modern data pipelines that deliver the critical business data needed to drive new sources of revenue, improve customer engagement and satisfaction, and fuel the next generation of AI and Machine Learning models.

Customer Challenges

  • Lack of access to all enterprise data and difficulty integrating between on-premises and cloud platforms creates data silos
  • Increased pressure for delivery of real-time insights to improve decision making, customer experience/channels, and applications
  • Legacy architecture is expensive to maintain and scale
  • Pressure to expand into modern technologies creates a need for a strategy and technology stack that will not isolate current investments

Differentiators

  • Real-time data streaming gives you fast access to fresh data when and where you need it
  • Build once, deploy anywhere model enables customers to build data pipelines in the cloud and deploy in any environment whether it be on-premises, cloud, hybrid, or multi-cloud
  • 50+ years of domain expertise in mainframe and IBM i systems
  • Easily integrate complex legacy data formats without the need for coding or specialized IBM knowledge
  • Strong partnership with industry leaders including AWS and Confluent

Customer Stories

Luxury Automotive Manufacturer (BMW)

Replicating data off of the mainframe to Kafka on AWS giving them the ability to scale and grow the business

Luxury Clothing Brand (Louis Vuitton)

Replicating data from IBM i to GCP (Google) in near real-time, improving logistics/supply chain

Citizens Bank

Replicating data from mainframe to Kafka on AWS to power modern digital banking experience

Capability Specific Discovery Questions

  • What data sources are you working with? What business value do these provide? What business applications do they drive?
  • What are your goals for evolving your IT architecture? What targets are you sending your data to? What are your use cases associated with these targets?
  • What gaps are you experiencing with your current data architecture today?

Data Quality & Observability

Continue the Story

… Driving confident data-driven decisions with data quality solutions that meet your unique business objectives helps reduce costs, boost revenue, increase compliance, and minimize risk. Precisely does this while minimizing business disruption and preventing costly downstream data and analytics issues.

Customer Challenges

  • Inaccurate, inconsistent, and unverifiable business data that leads to lack of trust in data, poor decisions and reductions in revenue and increased costs.
  • Lack of insight and understanding into the health of your data
  • Increased risks due to erroneous analytics that impact business decisions.

Differentiators

  • Broad and comprehensive data quality capabilities and expertise.
  • Integrated capabilities identify and resolve data quality issues as well as find, understand, observe, and enrich data.
  • World class geo addressing and reconciliation capabilities
  • Extensive deployment options and data sources for data in motion or at rest.

Customer Stories

Progressive

Reduce risk and improve accuracy by reconciling and tracking data as it moves across the enterpriseChanel: Manage data quality in Salesforce and ERP applications.

PNC Bank

Creating a 360 view of customer data to improve customer loyalty and identify risk

Capability Specific Discovery Questions

  • How confident are you in the accuracy, completeness, and quality of your data? Why?
  • What do you do if your critical business data is not complete or accurate? How often does this happen?
  • Tell me about your team’s data operations (DataOps) processes.

Data Security & Privacy

Continue the Story

… Such as defending against the increasing sophistication and complexity of today’s data security and privacy threats. Implement solutions and processes that help your organization establish and automate effective, comprehensive, and auditable practices.

Customer Challenges

  • Controlling access, maintaining data privacy, and monitoring behaviour.
  • Ability to meet visibility to ever evolving regulatory requirements.
  • Preventing malware threats which can lead to downtime, loss revenue, and increased costs.

Differentiators

  • Comprehensive IBM i expertise that integrates the global enterprise security requirements with the IBM i specific administration workflows.
  • Advanced MFA
  • Business friendly user interface that allows IT and business users to understand and track data privacy requirements

Customer Stories

Experian

Data is governed for over 22,000 customers to ensure GDPR compliance, and over 4,500 business, and IT users can now track critical customer data across over 1.2M production tables of metadata.

Capability Specific Discovery Questions

  • How do you prepare the employees in your organization who have responsibility for security and privacy?
  • Tell me what your company has done to prevent ransomware attacks.
  • Which data privacy concerns are top priority for your organization right now?

Geo Addressing & Spatial Analytics

Continue the Story

… Delivering accuracy with verified, geocoded, and enrichment-ready addresses and power decision-making with location-based context to improve resource allocation, enhanced customer experiences, and a more sustainable future.

Customer Challenges

  • Poor addressing leads to late and failed deliveries, incorrect taxes collected and an inability to leverage location data for process improvement.
  • Slow to recognize market trends, making it hard to recognize what is connecting with customers today or anticipate their needs.

Differentiators

  • Combination of hyper-accurate industry-leading global geocoding and enterprise location intelligence.
  • Business-friendly spatial analytics equipping users with context not found in spreadsheets to boost customers satisfaction and drive new business.
  • Easy enrichment of addresses with valuable context using a PreciselyID.

Customer Stories

Multinational retail corporation – Walmart

Accurate tax calculations preventing unnecessary tax overcharges and potential penalties

Global Outdoor Product Manufacturer – YETI

Improved overall brand insight across major sales channels

One of largest U.S. commercial property casualty insurance companies – Travellers
  • Travelers can run 1 million geocodes in
  • seven minutes and 50 concurrent real-time geocodes in
  • under 200milliseconds. This is more than twice as fast as
  • the insurer’s legacy systems
T-Mobile
  • Met compliance and regulatory
  • Requirements enabling them to receive federal RDOF
  • Funding, approx. $20 billion.

Capability Specific Discovery Questions

  • Explain to me where you know addresses or location data is being leveraged within your processes.
  • What are the teams/departments that are impacted with the address/location data?
  • What type of addressing are you working with today?
  • What is the cost of getting an address wrong?
  • How do you add context to address data? How do you make this context available to all users within your organization?

Master Data Management

Continue the Story

… Poor quality and inconsistent master data when siloed across multiple systems can be overwhelming. However, the pains of fragmented, ineffective data can be avoided with a Master Data Management (MDM) solution.

Customer Challenges

  • Lack of master data accuracy and consistency across data silos.
  • Inefficient customer relationship management due to lacking a 360-degree view of your customer; missing cross sell and growth opportunities.
  • Greater exposure to risk due lack of data quality of critical data across silos for accurate risk management.

Differentiators

  • Business friendly with a configure, not code approach.
  • Multi-domain MDM promotes cross-domain intelligence and increases adoption across teams
  • Open and extensible and built for scale, security, and performance.

Customer Stories

Fender

Single source to manage core product data, pricing, and product release packages

Thomson Reuter

Single source for customer, product, and accounting data assets

Capability Specific Discovery Questions

  • How is your organization currently managing and maintaining master data management across different lines of business?
  • How would you describe the current quality and consistency of your critical data, such as customer information, merchant, and reference data across business silos, partners, or channels?
  • How would your teams benefit if they have a more business-friendly, yet secure way to access master data?

Process Automation

Continue the Story

… The journey to data integrity starts with automating & streamlining processes for creating the highest quality data possible. Enable scalability by implementing solutions to ensure that the quality remains when you make changes or updates to that data.

Customer Challenges

  • Slow, error prone and manual SAP data entry leading to poor data quality & governance.
  • Steep learning curve requiring system expertise at all levels which causes a rigid and inflexible business.
  • Poor audit process increases business risk.

Differentiators

  • 20+ years domain experience.
  • Low-code/No-code resulting in minimal IT engagement needed.
  • Business user focussed with flexibility to choose interface for automating SAP master data.
  • Scalability across SAP landscape and connectivity through APIs

Customer Stories

Energy Drink Manufacturer
  • Excel-based data management process became a major bottle neck for their SAP ERP system.
  • Reduced time to market by between 50% and 75%.
Dorman
  • Material data changes manually would take about 60 hours per 100 materials and cost $4.5k due hiring & training.
  • Now takes about 5 hours with resulting in a 90% savings in both time and costs. Roughly $500k in the first year.

Capability Specific Discovery Questions

  • What SAP version are you running?
  • How do you handle workflows and approvals for SAP processes?
  • How do you create and manage SAP master data in complex, data-intensive processes?
  • What tools do you use for mass data maintenance/data migration scenarios?