Modern Data Management.
Classic Delivery.
Q Spark's proven modern data management solution methodology delivers business value fast.
Every time.
Delivering Modern Data Management
Q Spark Group is an innovative modern data management solution consultant. We have experience with all categories of data management solutions. For the past 25 years, our founders have modernized data management solutions. We increase data trust and utilization across your business.
There are lots of data management consultants. Q Spark Group is unique. Customer data is our specialty. We know how to use existing data tools to go beyond a customer 360 and sequence customer DNA – data, analytics and AI.
Our approach is different too. We believe in business-led technology strategy. We’ll utilize your existing data tools. We’ll suggest modern ones too, when necessary. What’s more, we’ll ensure your modern data programs are adopted by business users. And we’ll deliver business value.
AI is Disrupting Data Management
On-demand Webinar - Prevent AI from Creating Customer Mishaps
Why Data Governance is the Key
Without a filter, customer-facing AI could make mistakes. Embarrassing mistakes.
Learn how to govern data & AI together to prevent it.
Modern Data Management Solutions
Q Spark Group's Service Offerings
Effective Data Engineering
Cloud Data Warehouses, Data Lakes, Data Lakehouses, & Data Pipelines
Lots of organizations have established data engineering programs and deployed analytic data stores – cloud data warehouses, data lakes, data platforms, or data lakehouses. Yet very few data scientists and analytic users are happy with the data available.
We are experts in improving data engineering and data lakes/warehouses to make them more efficient. More important, we can make the data within them trusted, relevant and findable.
We understand how to utilize your existing data management tools and adopt modern ones to improve the data in your data engineering and lakehouses.
Operational Datastore to Run AI
Enterprise AI Apps Need Connected and In-context Data to Operate
When you are developing AI agents and co-pilots, you utilize centralized data from a data lakehouse. And then you put the AI agent into production and the data it needs comes from ….. uh oh.
Initially, most AI deployments are tied to a single ‘system of record’. AI agents within CRM, marketing and operational applications are deployed and use data from those applications. Even that is suboptimal – if AI is making decisions about customers, partners, suppliers with only partial enterprise data, it won’t be effective. AI that spans across functional apps would be impossible to operate.
Q Spark have a different POV. We believe you need an operational data store to operate enterprise AI solutions. And it will be unlike any operational data store you’ve built before. It needs to be virtual AND physical. It needs to process data centrally AND push processing down into apps. It needs to be componentized AND integrated. It needs to span multiple data domains AND integrate data from different sources. It’s not exactly MDM and its more than just a “360 view”. It’s a 3D view of all of your key organization data, available in real-time, and in-context for AI.
Modern Master Data Management
Cloud MDM Solutions, Advanced Entity Resolution, MDM Governance
Thousands of companies have invested in on-premise master data software. The need for integrated and trusted master data is stronger than ever before. Yet many organizations are not sure when, if, or how they will modernize MDM.
Q Spark understands how to modernize MDM. It isn’t just about implementing a cloud MDM solution. It’s about implementing a modern architecture to ensure master data is created and used throughout your organization.
We have deep expertise in MDM. Our founders built the first customer MDM product in the late 1990s, and we’ve innovated and modernized in the MDM market ever since.
Evolving Customer Data Platforms
Improving CDPs with Entity Resolution, MDM integration, & Composable CDP
Customer Data Platforms aren’t very good at identifying customers. Most focused on marketing functionality and activation, and relied on tags to identify digital prospects. The inability to match prospect and customer data limits the value of CDPs.
Q Spark are experts in entity resolution and MDM, and we have utilized these tools to improve the data within CDPs.
Our founders build the first CDP that specialized in first party entity resolution. We know how to match marketing prospect data with enterprise customer data to deliver your marketers relevant and in-context data for targeting.
Understanding, Improving and Governing Data
Data Governance, Data Catalog, & Data Quality
Data governance, catalog and quality technologies are designed for structured data. Many of them are struggle to fulfill their requirements for structured data, let alone the loads of unstructured data that’s used by AI.
Q Spark understands how to implement and extend these data tools to handle modern requirements for structured and unstructured data.
We have long experience in data governance, catalogs and quality – we’ve worked at major software vendors and drove their software strategy, and we’ve implemented these tools effectively.
Implementing Modern Data Architecture Styles
Data Mesh & Data Fabric
Too many data tools, not enough integration. Organizations are struggling to integrate tools to address modern use cases, which require on average 4 to 5 different data tools.
We believe in leveraging what you’ve got. We have a track record of utilizing existing data tools and extending them, and introducing modern data tools when necessary.
We have long experience in progressively modernizing data architectures. It’s complicated, and we like simplifying complexity. Our modern data architecture approach can deliver a data mesh and fabric iteratively, delivering business value to drive the program forward.
Creating Data Intelligence
Data Analytics & Enrichment
Why isn’t data pre-analyzed to create intelligence before data scientists use it? Foundational intelligence (segmenting customers, calculating customer interaction frequency, and so on) are done by individual analytic users over and over and over ….
We believe in being effective. Foundational data intelligence should be created automatically as data is being managed, and added to data sets before data scientists use them. Q Spark Group can take the data within your existing warehouse or lake and enrich it with intelligence that will improve analytic outcomes.
We have experience in enriching customer data sets to drive active and effective data science communities. We can make your data intelligent in a matter of weeks.
Data-Insight-Action Self-Assessment
The Q Spark Difference
The Q stands for quick. We believe in sparking innovation, and doing it quickly.
We are focused on the customer domain. It's more than just customer 360. Knowing your customer's requires a tight integration between data, analytics and AI technologies.
Execution is our calling card. Our Quick Spark methodology is designed for relentless execution on aggressive timelines, and we meet them every time.
Q Spark is known for our expertise. Our team are comprised of 25+ year veterans in data management and analytics, and experts in AI.
Customer DNA
You have to go beyond data and beyond a 360 to truly understand your customers. You have to know their DNA – Data, aNalytics and AI.
Customer data is everywhere. MDM. CDP. Data Warehouses. Applications. CRM. Despite significant investment in many technologies, customer data is still fragmented.
Customer DNA is delivered by multiple technologies. It requires a solution.
Q Spark Group are experts in customer data solutions. We can modernize your Customer 360 strategy and understand customers down to their DNA.
Is Your Customer 360 Feeling a Little Flat?
Modern Data Management for AI - On-demand Webinar
AI will disrupt every aspect of data management.
Learn 3 quick and cost effective ways to modernize data management in the coming year.
Our Customers Benefit from Modern Data Management
Luxury Hotel Chain
We implemented modern data governance, catalog and reference master data technologies to delivery trusted data for finance analysts.
US Insurance Company
We implemented a customer MDM/CDP hybrid to deliver a customer 360 for an analytics/AI program to deliver insights across sales, marketing, & service.
Global Technology Firm
We implemented a CDP with entity resolution to match customer & prospect data for billions of data records to execute micro targeted marketing campaigns.
Check Out Our YouTube Channel
Modern Data Management Solution Videos
AI is Disrupting Data Management - David Corrigan Shares his POV
MDM Modernization 5 Best Practices to Avoid Common Pitfalls - Sachin Wadhwa Shares His Experiences
Why Should You Modernize MDM - Sachin Wadhwa's POV
Are You Stuck with IBM MDM?
Blogs on Modern Data Management Solutions
Tips, Tricks and Best Practices on Modernizing Your Data Management Technology
It’s Time to Start Governing Data and AI Together
Governing data and AI together is better than governing data and using it for AI. It’s required for compliance. It’s necessary for customer relationship management.
What is Data Modernization?
Data Modernization is a continual business strategy that drives utilization of data across the enterprise and evaluates progressively modern technologies to better manage data.
The Current State of MDM – Part 4 – How Integrated, and Integral, is MDM?
Modern MDM solutions have impressive Data Quality functionality. But do they have impressive data quality? Maybe it’s time for their relationship to evolve.
The Current State of Governance of AI and Data