“So nice to see you, Ramya! Thank you so much for the Data-as-a-Service guidance. We have more or less decided to go for it, and I need you to fill me on more details. Monetizing data – as you had mentioned last time.”
“It’s a smart way of tapping the potential of your data to create a new revenue source. You’ll wonder why you never thought about it!” I laughed as we sat down. “As you know Janine, DaaS works for streaming data in real-time from anywhere in the world and from any device, delivering consistent data quality and agility. Naturally you pay for accessing the data. Now suppose others pay you for accessing your data?”
“With DaaS, you need not be a data consumer alone, you can be a data provider, too.”
“That is wonderful!”
“It is indeed. In the data economy, you have invested so much in creating a great asset, your enterprise data. How about licensing it for use by others? That is Data Monetization put simply.”
“That sounds really exciting. Being in Pharma, we consume huge volumes of data, but we also generate equally large data.”
“Trust me, data is the most exciting thing happening today, and it’s high time you participate in monetizing it. Reltio DaaS makes it very easy to fast track your data monetization. You already have quick access to datasets readily available from data tenants in the cloud. You have a single reliable source of data that is continuously updated and refined. Choose one or more from the multiple engagement models we provide, and you are ready to go. The simplest is the Data Store-front where users can search and browse data, and download by paying.”
“Another model is List Match Service, a stand-alone service to provide ad hoc matching, enrichment, and validation. You can also consider Data API Services, which are custom services for a particular data domain. For example, HCP credential verification in the Healthcare and Life Sciences vertical where you operate.”
“Lots of options, more than I had thought.”
“Yes. Moreover, to help you monetize your data quickly, we have a robust API platform for custom services and embedded experience. In fact, we can help you set up in all four models, including MDM Data Subscription, which is the data delivery to MDM tenants.”
“Let me discuss with our people which way we should go.”
“Right. If you choose to go with Reltio, I promise you don’t have to run around as we take care of everything. We help onboard new customers much faster and we can enrich data via list match service. Being integrated with Reltio’s modern and scalable platform for continuous data quality and delivery, you can quickly implement any changes to data. And guess what, we have a convenient pay-as-you-go billing method. As your customers increase, you can also look forward to reducing distribution and operating costs.”
“So I guess everything is set up!” Janine was happy with the thought of generating revenue from enterprise data. Who wouldn’t be?
“Just one more point. I suppose complete tracking is part of the service.”
“It is. You can track attribute level audit, history, and lineage of all data usage and changes. Track record-level and attribute-level consumption patterns. Track a variety of contributing data sources for ongoing updates and downstream data distribution. And you don’t have to worry about strong data security and privacy regulations. Reltio platform is HITRUST CSF-certified, and GDPR compliant.”
“Very comprehensive and competent. These coffee sessions are turning out to be amazing for me!”
Like Janine, several customers have benefited from Reltio’s fast-tracked data monetization, extending their quality data to drive revenue for the organizations. How about you?
Reltio Supports Apple CEO Tim Cook’s Clarion Call for Stronger US Customer Data Privacy Laws
Manish Sood, CEO & Founder, Reltio
Apple CEO Tim Cook’s call for a U.S. privacy law, similar to GDPR (General Data Protection Regulation), is appropriate and timely. Five years ago this initiative would have been too big of a burden for companies because customer data is siloed throughout organizations in dozens or hundreds of separate systems. But today modern data management solutions that include technologies like machine learning empower organizations to implement data governance and privacy initiatives at scale, and are an essential part of their overall Customer 360 data strategy.
GDPR has irreversibly changed the landscape for single customer view data projects for companies doing business in Europe. And there are lessons we can learn from businesses that have gone before us. Early efforts to comply with data mandates at the application level have come up short. Upholding GDPR principles, as companies have quickly realized, requires an enterprise data layer approach to PII (Personal Identifiable Information).
Virtually all companies have customer data scattered across multiple networks and lines of business — the only way to manage this data sprawl so that customer data privacy compliance is assured is to discover, organize and control all customer data from internal, external and third-party sources. If that sounds like a tall order, the good news is that we at Reltio have already developed and implemented best practices that include the essential ingredients for ensuring customer data privacy for some of the largest global enterprises by:
Identifying all systems managing customer data
Blending different types of data
Understanding data ownership
Identifying data shared outside the organization
Maintaining data lineage across all customer attributes
Managing different types of consent, and their sources
Providing customers a way to make data-related requests
Deploying processes for required data access, change and deletion
Implementing a mechanism in place for timely reporting of a data breach
Whether it’s correlating omni-channel transactions to customer master records and understanding, to determining how each customer is related to other members of a particular household, to whether those disparate household members have consented to their data being used and for what purpose. Maintaining data lineage to data sources and tracking to downstream applications so we know from where a customer profile attribute originated and which applications are using it is critical. This is the power of technology that enterprises already have to ensure customers are protected under the right to be forgotten stipulation. (As an aside, the right to be forgotten is a bit of a misnomer. The regulation actually stipulates that a company is required to retain evidence that they ‘forgot’ a customer. Make sure you pick a vendor who understands these nuances or your efforts may be undermined.)
Under GDPR, individuals are entitled to data erasure, which means that at their request, all traces of their information must be purged, including legacy transaction data that might reside in activity logs. In sum, this mandates a comprehensive customer profile with a 360-degree view that can accommodate data-change requests and the ability to generate privacy compliance reports fast.
Organizing data with a modern data management platform for growth strategies like new revenue models, improved customer experience, or other initiatives results in clean, reliable data with built-in customer data privacy compliance.
A comprehensive customer-centric data management strategy that delivers data privacy capabilities is built on four pillars:
Consolidated profiles: Organizations need the ability to collate all data from internal, external, third-party and social sources. At the same time, they must have the power to trace and maintain data lineage across all attributes. This sweeping level of visibility is invaluable in the event of a data breach.
Managing relationships: Graph technologies play a unique role here — they offer a deeper and more accessible understanding of relationships between stores, locations, channels and types of consent. It also helps to trace the adult consent for capturing the data of a minor.
Data change requests: This is a critical requirement for GDPR compliance, and companies need to step up. Built-in workflows in the systems used should accommodate all customer data change requests, deletion requests, review requests and more.
Data as a Service with traceability: Drawing from third-party sources is a major benefit, but GDPR compliance requires tracking which attributes came from where.
Those that view a U.S. privacy law as a regulatory burden rather than an opportunity have not yet internalized what it means to be a customer-driven company. Your customers’ privacy is already table stakes today and is part of your responsibility as you serve them. Compliance towards protecting customers’ privacy is a journey not a destination – get the right platform in place today so you can meet any regulation or concern that they might have. You’ll find that it will improve your brand, and customer loyalty, and that’s just good business.
I’m proud that Reltio has been a pioneer in empathizing, understanding, anticipating and embracing customer privacy concerns, and that we’ve embedded product capabilities into our Reltio Customer 360 solution. I completely agree with Tim Cook’s call for a similar U.S Privacy law and as Reltio customers can attest they are already ahead of the game, with Reltio governing their sensitive customer data at scale throughout their organization using master data management, graph, and machine learning technologies.
Why Reltio is All-in on Salesforce Customer 360, and the Adobe, Microsoft, SAP Open Data Initiative
Manish Sood, CEO & Founder, Reltio
Last week we saw some exciting announcements on the subject of Customer 360 and customer engagement. First Adobe, Microsoft, SAP and announced a new partnership: the Open Data Initiative, the intention to create a single data model for consumer data that is then portable between platforms. Then Salesforce announced Customer 360 at Dreamforce 18, to help brands identify who their customers are and how they previously interacted with them. The single customer 360 ID will enable companies to access customer information through Salesforce’s various applications including Sales Cloud, Service Cloud, Marketing Cloud, and Commerce Cloud.
The announcement is great news for the industry, and I’m excited to share today that Reltio will be supporting both initiatives. This means that our customers, who are already in production using Reltio Cloud for Customer 360, as well as any future customers and partners, will be able to use Reltio to take full advantage as both initiatives evolve while benefiting from significant additional capabilities.
Standardizing on a common data model, and having a single Customer 360 ID is important, but such efforts have historically been limiting. Common IDs and tight coupling of apps can solve some immediate problems, could provide a quick fix for small organizations but in the long run, can create new islands of data that can create challenges for larger enterprises. Reltio will help both initiatives by continuously unifying and organizing all data within their respective models while making it universally accessible for collaboration and consumption across the enterprise. Our philosophy has always been that standalone customer profile data reconciliation is insufficient without the benefit of understanding relationships across more than just the customer domain. Unlocking the value in relationships across multiple domains such as customers, households, stores, locations, products, parts, suppliers is essential to a true Customer 360, and Reltio delivers this at an enterprise scale.
The Open Data Initiative announcement mentions a data model with over 50 different open source schemas stored in a data lake. These schemas require companies to stitch together the relationships across attributes, schemas, and profiles. Reltio helps this effort through logical metadata that combines all 50+ schemas into one unified canonical model and view of the customer data while ensuring continuous data quality that prevents a traditional data lake from turning into a data swamp.
We started Reltio on the idea that customer data will always be distributed across dozens of application sources with different formats; that companies will keep on adding new sources; that understanding relationships across all data types, not just customer profiles are important; that agility is key, and that future-proofing from changes in technology investments is critical. It’s the reason why we adopted a multi-cloud, multi-model data storage architecture, rather than an arguably easier approach of committing to a single NoSQL, RDBMS, or a graph database. For over seven years, we’ve been delivering on the promise of the complete customer 360-view, through a foundation of trusted, reliable data, powered by open, next-generation modern Master Data management (MDM). We’ve delivered this by not just creating a better MDM in the cloud, but creating a true 360-view that includes master data, relationships across all data entities and correlating omnichannel interactions, transactions. But we didn’t stop there. We architected a platform that brings together analytical insight and operational execution using advanced analytics and machine learning to continuously correlate insight, action, and outcomes in a closed-loop, to extract the maximum business value out of data.
Our customers – which include eight of the 10 largest life science companies, two of the top 10 cosmetics companies in the world, a global hotel and hospitality group, a U.S.-based healthcare insurer, one of the largest U.S.-based pet retailers, one of the largest mortgage providers – rely on Reltio for their digital transformation and customer engagement initiatives. From globally harmonizing customer 360-views across 140+ countries to bring together customer data from hundreds of millions of organizations, to real-time personalization, marketing segmentation of millions of consumers, Reltio continues to deliver on the promise of Customer 360.
Speed, performance, and scalability are key. Over 4.3 billion mission critical master profiles, representing well over 1 Petabyte of storage under management in Reltio Cloud, is being accessed by business teams globally to the tune of over 85 million real-time API calls per day. As these numbers are growing by the second, our multi-cloud platform supported on both AWS and GCP provides the elastic and scalable horsepower to meet demanding workloads, and the aggressive growth objectives of global enterprises. They look to their “Reltioed” data as the trusted source for their analytics and machine learning (ML) initiatives, compliance requirements such as GDPR, and next-generation customer engagement and experiences.
Reltio partners, including Salesforce, Mulesoft, IQVIA, AWS, GCP, Accenture, Cognizant, Wipro, ZS Associates, and Dun & Bradstreet, have all been part of successful Reltio for Customer 360 deployments, which bring together data across applications and sources in multiple Salesforce, Adobe, Microsoft, and SAP environments.
These are exciting times for enterprises looking to transform themselves and leapfrog the competition. But it’s not easy, with a shifting landscape of technology choices, continuously evolving regulations such as GDPR, CCPA (California Consumer Privacy Act), and the need to operate at scale most cost-effectively. To companies considering how the Salesforce and Open Data Initiative announcements might impact their plans, please reach out to us to learn more about our support of both initiatives, and how we can get you on a path to future-proofed Customer 360 in a matter of weeks. To our current customers who have placed their faith, and most importantly their critical customer data assets into Reltio, I’d like to say thank you, and assure you that the best is yet to come.
On May 25, 2018 GDPR (General Data Protection Regulation) went into effect. The primary objectives of the GDPR are to give control back to their EU citizens and residents over their personal data, to simplify the regulatory environment for international business, and to unify regulations within the European Union.
GDPR is relevant for any organization doing business with EU citizens, regardless of where the company is based. Personal data includes a wide range of personal identifiers, from addresses and public information, to social profiles, images, IP information, device IDs and medical and financial details.
Consumer personal data collected within your company is often distributed to multiple systems and organizations, resulting in duplication. Your organization may be considering master data management (MDM) solutions to address various data management needs including compliance challenges. Legacy MDM systems may comply with a small part of the regulation by managing profile data, but they also leave it to you to figure out how to manage the transaction and interaction information distributed across systems and channels.
Complying with GDPR should be part of your day-to-day operations. One philosophy is that a Modern Data Management platform should organically support the key elements of GDPR by managing your customer’s profile information, lineage and succession through your day-to-day data management activities.
RIGHT TO BE FORGOTTEN – GDPR guidelines require your organization to support your customer’s Right to be Forgotten and purge their records upon request. Your business will also need to support your customer’s request for a copy of their information in a portable format. Any GDPR solution needs to guarantee purging of all traces by customer entity type in support of data erasure, including the removal of any attributes and historical transactions made by individuals captured as part of their digital activities, which is outside of the scope of traditional legacy MDM tools.
CONSENT MANAGEMENT – Your company must also support a provision to produce any proof of consent provided by your customer on request, and a way for customers to withdraw the consent. Explicit consent is required before information is collected, and adult consent is mandatory when the collection of data involves children below the age of 16 years. Any solution that supports the management and maintenance of rights and consents must have the ability to capture and store consent types. Graph technology provides a great way to store relationships so you can easily capture and prove that an adult provided consent regarding the collection of information for a minor.
AUDIT & LINEAGE – The new GDPR legal framework requires your company to support the ability to demonstrate the deletion of your customer’s private information. built-in audit and data lineage to support accountability for your business to demonstrate compliance. Attributes must also traceable back through lineage to the internal and external data providers they came from. In the case of a change request, the request can be routed back to its original source.
Facebook has stopped short of promising GDPR level data compliance for US users. If you are a US company, even if you have no EU data, you should consider implementing a Modern Data Management platform that gives you GDPR-ready capabilities. Imagine the branding and goodwill you’ll get with your customers when they realize that you are taking measures above and beyond (exceeding that of Facebook) to respect their privacy and data.
Finally it won’t take long for the US and rest of the world to catch up, the State of California recent enacted The California State Assembly’s passage today of the California Consumer Privacy Act (CCPA) which has many elements of GDPR. My article listed three very basic GDPR requirements, there are certainly many many more. Regardless of the solution or tool you put in place today you know that many more regulations are coming. A Modern Data Management platform does the heavy lifting for you today, and protects you into the future, allowing you to focus on your business.
A modern Master Data Management (MDM) Platform helps businesses manage data like leading digital companies, leveraging continuous data organization and recommended actions to measure and improve their operations. Here are the seven reasons why enterprises should invest in a modern MDM Platform to drive ongoing business value.
1. Reduced IT & Operational Cost
A leading PC & printer manufacturer & re-seller created a single global view of accounts. Reltio Cloud delivered an Account 360 solution to manage complex relationships and hierarchies among their business units, customers, and partners. It helped the client improve their territory alignment, multi-channel campaign execution, and field incentive compensation planning. Reltio has helped increase their data load performance by 577X and is expected to save them more than $12M over 5 years through improved IT and data management operations.
2. Increased Productivity
A top 5 global pharma reduced cost of ownership by $3.6 million per year, and improved user query response time by 10X. Reltio Cloud was deployed to replace the client’s 67 MDM on-premises instances with just 3 regional cloud tenants. It allowed them to execute multi-channel marketing campaigns and simplify capabilities for cross-market queries on healthcare providers (HCPs). With Reltio Cloud’s simple configurability and ease of use, the business teams were able to give its field sales reps the ability to submit updates through the Reltio UI via mobile phones, allowing them to contribute towards overall data quality.
3. Fast Path to Digital Transformation
A top used car retailer consolidated data from 155+ store systems in less than 15 weeks to drive omnichannel customer experience. Reltio Cloud supported a Consumer 360 solution, managing the client’s multi-domain data (customers, vehicle stores, accessories) in a holistic manner while integrating real-time predictive analytics with full visibility into all customer interactions. The Customer and Vehicle Master helped the client’s marketing team execute better targeted campaigns and allowed the merchandising department refine inventory acquisition targets based on more complex demand analysis.
4. Enabling Connected Experiences
A leading pet specialty retailer leveraged data to tackle Amazon Effect and transform into a customer-centric service company. Reltio Cloud delivered a Consumer 360 solution that supported a single view of pet parents across all the client’s brands, joint ventures, and multiple systems. Reltio’s unique approach to modeling relationships with graph technology, combined with big data science, enabled the client to unlock the critical intersections of interactions and information by creating a single repository of trusted and mastered pet parent profiles in real-time.
5. Built-in HIPAA Compliance
A leading health insurer created a single view of their members across multiple systems to execute a member-centric omnichannel strategy. Reltio Cloud enabled a Member 360 solution, providing visibility into the entire touch-point history for each member and optimizing member experience while meeting HIPAA compliance requirements. It helped the client do segmentation, targeting, and direct-to-consumer (DTC) campaigns with higher precision. With Reltio’s cloud-based platform, flexible modern data architecture, and agile deployment the client delivered lower TCO and quicker time to value for their IT, sales, and marketing teams.
6. Speed to Value
An American diversified global insurer created a holistic view of their brokers for better segmentation, compensation elasticity and retention analysis, all in four weeks. Reltio Cloud for Account 360 helped the client create a single view of their brokers (firms and captive agents) for effective commission management. Reltio’s Self- Learning Graph capability enabled the client uncover relationships among brokers, distribution channels, products, employers and insured employees to identify top brokers and find upsell and cross-sell opportunities.
A global colocation provider ensured the ‘Right to be Forgotten” for their customer contacts with an implementation that took twelve weeks. Reltio Cloud for Account 360 helped the client create a single view of their enterprise customers with built-in audit, data lineage, and workflows. It ensured ongoing purging of all traces by customer entity type in support of data erasure, including the removal of any attribute, historical activities made by individuals and activity logs on the Reltio Platform. In addition, Reltio Cloud’s Self-Learning Graph enabled them to reveal relationships among people, products, locations, and consent types.
The simple answer is that the Wave’s qualification criteria includes several key areas in which Reltio is naturally strong. As the only Master Data Management platform recognized in the Wave we believe our core MDM capabilities contributed to our strong showing. In fact, Reltio had already been included, together with 23 other excellent companies, in Forrester’s Now Tech: Machine Learning Data Catalogs, Q1 2018 report preceding the Wave.
That report outlined key 3 characteristics of Machine Learning Data Catalogs (MLDC):
1. Interpret, define, classify, link, and optimize the use of disparate data sources
Reltio is used by companies globally to define logical business schemas, capture and discover relationships through the Reltio Self-Learning Graph, suggest ongoing improvements, and to organize and bring siloed data together across the enterprise to meet their business objectives. This continuous reliable data foundation feeds better operational execution, predictive analytics, and sets them up to evolve towards a self-learning enterprise.
2. Reconcile policies across data use
Reltio Cloud’s built-in data security and privacy, regulatory, life-cycle, and data quality policies coexist to adapt data for multiple uses through a powerful audit trail, and role based access to data. This is critical in the face of evolving compliance measures such as GDPR. Flexibility and agility to ensure that you can track not just where the data originated, but how it’s being used and the outcomes it generates, is a critical component of any forward looking ML strategy.
3. Democratize data to the edge of business
Reltio is particularly well suited to meet this requirement through frontline business user facing data-driven applications and workflow and collaboration capabilities that come OOTB with Reltio Cloud. It allows teams to submit comments, suggestions, filter and easily segment information through a UI that’s as easy to use as Facebook and LinkedIn.
Data science teams are then able to use Reltio IQ, with Apache Spark to run their algorithms without the pain associated with cleaning and onboarding data in separate environments. This is increasingly important as enterprises deploy machine learning systems, with data scientists requiring relevant, curated data sources to train algorithms to improve results.
As this video illustrates, the true value comes from being able to synchronize ML-algorithm derived IQ scores back into master profiles as aggregate attributes. Making them available for segmentation by marketing, sales, and even data stewards and compliance teams. Teams can then continuously reconcile results to recommendations in a closed loop to self-learn and improve outcomes.
We are tremendously proud and honored to have been included in the MLDC Wave as it reflects our core belief that machine learning cannot be used in isolation from the overall data organization and management needs of the business.
Whatever your desired outcome, MDM forms the backbone of high quality, reliable data which allows ML to thrive.
ML in turn provides unique capabilities to improve and increase the efficiency of data quality, and enterprise data organization operations. Like the graphic I selected for this post, they go hand in hand, and are interconnected across all points of the data continuum and life cycle.
Post May 25, 2018, per the General Data Protection Regulation (GDPR), companies with business ties to the European Union need to comply to GDPR standards. The cost of non-compliance is huge, but the regulation is meant to benefit individuals as well as businesses. Let’s look at what it can unlock for you and your brand if you approach it in the right way. What about being able to say that you are the safest enterprise in your marketplace when it comes to data? How about if you can not only reduce operational cost but can also create new revenue streams by being compliant to GDPR and other upcoming regulations?
1. Replace Legacy Systems by Future Proof Cloud-based Applications
When companies are taking steps to comply with GDPR, they are required to perform a ‘spring clean’ of their data, which can in turn lead to multiple efficiency gains. Organizing data improves the way firms carry out analytics and take business decisions. To comply with the regulation, companies must be able to illustrate the entire data flow – how data comes into the company; how they store and manage it; and how they treat it at end of life. This will encourage businesses to replace legacy systems by flexible cloud services to be more nimble and transparent especially when regulatory regime keeps evolving. In addition, most large enterprises have grown through M&A. Thus, they can look at GDPR as an opportunity to get rid of obsolete software and accelerate application retirement.
2. Gain Brand Loyalty and Attract New Customers
Companies can leverage GDPR to change the landscape from risk mitigation to improving their long-term competitive advantage. They can see early GDPR compliance as a competitive differentiator and position themselves as leaders of an emerging new normal. We trust those businesses who values our privacy beyond mere legal compliance. Thus, GDPR is an opportunity for businesses to get their data in order, get compliant and become consistently transparent with their customers. In a post-GDPR world, data sharing would be seen in the context of mutual respect and value exchange. It is an opportunity to re-connect your business with your current and potential customer base and start a new relationship based on mutual trust and responsible personalization.
3. Invest for the Future
The criticism that GDPR compliance might restrict innovations in AI ignores a subject’s right to privacy and consent. In fact, not being GDPR compliant would impose far more constraints on data collection and processing, slow down the ability to leverage innovations in AI and pay an opportunity cost such as market share losses in the future. Read this article for more details – Understanding GDPR and Its Impact on the Development of AI. In addition, in an era of data-driven innovation, business partners need to work together across the value chain. Data-driven innovation requires a clear understanding of the data to be collected and the reasons for collecting it. There are double opt-ins in such value chain: both partners need to be clear about what data they have about each other, and why. It’s very important that their data sharing practices are compliant with GDPR and other upcoming data regulations. As a first step to GDPR compliance, companies must define the scope of GDPR-relevant personal data that is collected, processed, and shared. Once a company identifies the scope of GDPR-relevant personal data, it should catalog all internal and external data sources that fall within this scope.
4. Execute A Delicate Interplay of Offense & Defense Data Strategies
In the post-GDPR era, personal data protection will become a data strategy issue. To comply, businesses need to have solid data organization and data governance in place. The GDPR gives companies the opportunity to holistically re-assess all their data, not just personal data. Data defense is about minimizing regulatory risk and preventing theft. Data offense focuses on increasing revenue, profitability, and customer satisfaction. Strong regulation in an industry (e.g. financial services or health care) would move the company toward defense; strong competition for customers would shift it toward offense. The CDOs and the rest of the leadership should see GDPR as an opportunity to establish the appropriate trade-offs between defense and offense to support company’s overall strategy. Read this blog post for more details – Is Your Data Strategy Defensive or Offensive? Why Not Both?.
Data is a company’s most important asset, and it’s constantly growing. Taking mandated compliance and turning it into an opportunity to personalize, delight and exceed customer expectations would fuel innovation reliably and responsibly.
Modern Data Management Summit 2018 Welcomes Enterprises to the Self-Learning Era
What an exciting data summit to be a part of. As Richie Etwaru, CDO of IQVIA put it, we are still having the intellectual hangover from the event. As a Diamond sponsor of the summit, it was a great pleasure for us at Reltio to welcome all attendees, sponsors, and speakers to what has proven to be the largest gathering of data management leaders and practitioners.
Held on February 26-27 2018 in San Francisco, the second annual summit had over 40 sessions and panels, 60 speakers, and 19 leading data management enterprises as sponsors. There was never a dull moment during the conference. This year there were three tracks – Modern Data Management, Healthcare & Life Sciences, and Artificial Intelligence and Machine learning. Tracks covered a wide range of top of the mind topics such as Master Data Management, Reference Data Management, Big Data, AI and Machine Learning, Advanced Analytics, Data as a Service, and Blockchain.
Presentations and demo sessions reviewed the most advanced solutions for Digital Transformation, Customer Experience, Consumer 360, Account 360, Supplier Management, Product Management, Data Monetization, and Compliance (GDPR, KYC.) Hundreds of senior IT and business executives from life sciences, healthcare, media & entertainment, hospitality, retail, financial services and technology corporations joined to witness and discussed the latest advancements in data management.
The highlight of the event included the introduction of the latest version of the Reltio Self-Learning Data Platform with Reltio CEO Manish Sood kicking off the conference by delivering the keynote address: The Self-Learning Enterprise Era. Learn more about Self-Learning Data Platform by reading this whitepaper. Michele Goetz, Forrester Research Principal Analyst reviewed how “Machine Learning Puts Data Front And Center For Business”, exploring why the technology must operate at the heart of a data strategy, not only at the edge, and detailing how enterprises are turning from data as an asset to data as a business.
Summit also recognized the smartest and most innovative IT and business professionals with The Data Genius Awards. The recipients have blazed the trail for their creative use of data for the benefit of their companies raising their Enterprise Data IQ every day through continuous Data Organization and Self-Learning.
It was not all work but plenty of fun as well! Attendees joined the evening reception and tried their luck at the casino night, keeping their commitment not to gamble with their data! Some quick snippets from the event are captured in this video.
Overall a great event with excellent sessions that offered new ways companies must think about their data to be competitive in the new digital economy. Companies are beginning their journey towards a Self-Learning Enterprise starting with the organization of data of all types and sources at scale to form a trusted data foundation. They are leveraging analytics for operational execution—simple business rules or machine learning algorithms tuned by data scientists—to deliver recommended actions and aspiring to become the Self-Learning Enterprise that measures the outcomes of those actions and use data in a continuous cycle of improvement.
Selected session recordings from the event will be available soon. Submit your request to access the session videos from the Summit here. If you missed the event this year, watch this space and we will announce the next summit soon! See you at #DataDriven19
Here are a few predictions and perspectives from industry experts to learn from and be smarter this year:
The Promise of Artificial Intelligence (AI) and Machine Learning (ML) Continues on
There have been repeated predictions over the last couple of years touting a potential breakthrough in enterprise use of AI and ML. This year is no different as the potential benefits from adding some kind of intelligent AI/ML layer to software emboldens more organizations across industries to adopt these technologies.
ML and predictive analytics are leveraged to suggest next-best-actions for sending relevant and timely information to customers and finding opportunities for up-sell and cross-sell. Insights like churn propensity, life-time-value, preferences and abandonment rates can be delivered to relevant teams, along with recommended actions that allow them to capitalize on this information.
Effective May 25, 2018, the European General Data Protection Regulation (GDPR) will force organizations to meet a standard of managing data that many won’t be able to fulfill. They must evaluate how they’re collecting, storing, updating, and purging customer data across all functional areas and operational applications, to support “the right to be forgotten.” And they must make sure they continue to have valid consent to engage with the customer and capture their data.
Meeting regulations such as GDPR often comes at a high price of doing business, not just for European companies, but multinational corporations in an increasingly global landscape. Companies seeking quick fixes often end up licensing specialized technology to meet such regulations, while others resign themselves to paying fines that may be levied, as they determine that the cost to fix their data outweighs the penalties that might be incurred.
With security and data breaches also making high-profile headlines in 2017, it’s become an increasingly tough environment in which to do business, as the very data that companies have collected in the hopes of executing offensive data-driven strategies, weighs on them heavily, crushing their ability to be agile.
Customer-obsessed, Data-driven Retailers will Thrive
With the Cloud Infrastructure as a Service (IaaS) wars heating up, players such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure continue to attempt to outdo each other on all vectors including capabilities, price, and service.
To avoid being “Amazoned,” some retailers have even adopted a non-AWS Cloud policy. For most, however, it’s about efficiency and cost. Multi-cloud means choice and the opportunity to leverage the best technology for the business challenges they face.
Today’s Modern Data Management PaaS are naturally multi-cloud, seamlessly keeping up with the best components and services that solve business problems. Acting as technology portfolio managers for large and small companies who want to focus on nimble and agile business execution, these platforms are democratizing the notion of multi-cloud for everyone’s benefit.
The Deck will be Cleared for Accelerated Enterprise Digital Transformation
The business landscape is changing like never before. New revenue models, new competition, newer regulations and exceeding customer expectations are forcing organizations to rethink how they do business.
Digital transformation is one of the key initiatives for many organizations looking for ways to leverage digital technologies, become agile, more productive and above all, provide a connected digital experience for their customers. For digital transformation to succeed, a solid data management foundation is a must.
Today’s Modern Data Management Platforms as a Service (PaaS) seamlessly powers data-driven applications, which are both analytical and operational, delivering contextual, goal-based insights and actions, which are specific and measurable, allowing outcomes to be correlated, leading to that Return on Investment (ROI) Holy Grail, and forming a foundation for machine learning to drive continuous improvement. As an added bonus, multi-tenant Modern Data Management PaaS in the Cloud, will also begin to provide industry comparables, so companies can finally understand how they rank relative to their peers.
With the emergence of IDNs, ACOs and MCOs, the approach to healthcare is evolving. The focus is on overall well-being and quality of life, rather than a one-time treatment. This requires a new patient-centric approach, complete understanding of the patient’s needs, behaviors and preferences, and focus on building long-term relationships.
In this changing healthcare environment, a modern approach to data management that enables complete understanding of patients, physicians and other partners across all clinics and facilities, while guaranteeing HIPAA compliance is necessary.
Whatever the industry or business need, most enterprises will need to first focus on IA (Information Augmentation): getting their data organized in a manner that ensures it can be reconciled, refined and related, to uncover relevant insights that support efficient business execution across all departments, while addressing the burden of regulatory compliance.
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