Introduction

“Big Tech” — the technology giants and market leaders led by Amazon, Apple, Alphabet, Microsoft and Facebook — have entrenched themselves as the sole proprietors of your data. These five companies alone have hauled in a staggering USD 900 billion of revenue in 2019.

If we add to this the revenue of other dominant technology companies competing in this space, such as Salesforce, Oracle, SAP, Adobe, and others, we are easily looking at a total annual revenue of well over USD 1 trillion, comparable to the annual GDP of countries such as Indonesia, Mexico, or Spain.

The usage and protection of personal data and privacy have increasingly come into the focus as more sophisticated users demand transparency on how their personal data is being used and safeguarded by institutions and businesses alike.

Big Tech maintains their dominant market position by collecting data across all of their services from consumers and businesses alike. Then, they use the collected data to sell access to consumers back to the businesses.

Application owners and developers are locked into their walled gardens and are tethered to poor interoperability and high dependence.

The existing reliance on Big Tech within the enterprise data market needlessly exposes their customers to risks related to data privacy, compliance and security.

The lack of alternatives gives the Big Tech companies a lot of leverage over a captive market, with barriers to decouple from this arrangement remaining prohibitively high. Business owners and application developers alike are, however, tied to these data silos when creating new products or services.

The majority of the business owners and developers who have to play by the rules (and fees) of these walled gardens are struggling, and are frustrated with the present situation.

All of these existing issues confront businesses with the question of how they can develop cost-effective and efficient first-party data solutions that will allow them full control over their data, coupled with tools to collect and process data to extract applicable insights in a secure and compliant fashion. While Big Tech is fighting tooth and nail to preserve a monopoly in customer data management and monetization, a new age of decentralized, peer-to-peer and ethical customer data ecosystems is breaking out on the horizon.

What Is Data Governance?

Broadly speaking, data governance is the process of managing the availability, usability, integrity and security of the data in enterprise systems, based on internal data standards and policies that also control data usage — simply put, how user data is managed and used by the organization. Effective data governance ensures that data is consistent, trustworthy, and doesn’t get misused or compromised.

A Breakdown of Data Governance

  • First, data governance is a cross-functional effort. It enables collaboration across boundaries and data subject areas.
  • Second, data governance is a framework, which provides structure and formalization for the management of data.
  • Third, data governance focuses on data as a strategic enterprise asset. Data is the representation of facts in different formats.
  • Fourth, data governance specifies decision rights and accountabilities for an organization’s decision-making about its data. It determines what decisions need to be made about data, how these decisions are made, and who in the organization has the rights to make these decisions.
  • Fifth, data governance develops data policies, standards, and procedures. These artifacts should be consistent with the organization’s strategy and promote desirable behavior in the use of data.
  • Finally, data governance monitors compliance. It includes the implementation of controls to ensure that data policies and standards are followed.

Data governance is one of the top strategic initiatives for global organizations today. Since technology trends such as machine learning and artificial intelligence (AI) rely on data quality, with the push of digital transformation initiatives across many global industries, this trend is likely not going to change any time soon. The growing data volumes from diverse sources cause data inconsistencies that need to be identified and addressed before decisions are made based on incorrect data.

Companies introduce more self-service reporting and analytics, which create the need for a common understanding of data across the organization. The continuing impact of regulatory requirements such as the General Data Protection Regulation (GDPR) increases the pressure on companies to have a strong handle on what data is stored where, and how the data is being used.

Benefits of Good Data Governance

Benefits of having well managed data governance for an enterprise are many, including:

  • Make consistent, confident business decisions based on trustworthy data aligned with all the various purposes for the use of the data assets within the enterprise;
  • Meet regulatory requirements and avoid fines by documenting the lineage of the data assets and the access controls related to the data;
  • Improve data security by establishing data ownership and related responsibilities;
  • Define and verify data distribution policies including the roles and accountabilities of involved internal and external entities;
  • Use data to increase profitability. Data monetization starts with having data that is stored, maintained, classified and made accessible in an optimal way;
  • Assign data quality responsibilities in order to measure and follow up on data quality KPIs related to the general performance KPIs within the enterprise;
  • Plan better by not having to cleanse and structure data for each planning purpose;
  • Eliminate re-work by having data assets that is trusted, standardized and capable of serving multiple purposes;
  • Optimize staff effectiveness by providing data assets that meet the desired data quality thresholds;
  • Evaluate and improve by rising the data governance maturity level phase by phase;
  • Acknowledge gains and build on forward momentum in order to secure stakeholder continuous commitment and a broad organizational support.

The Future of Decentralized Enterprise Data

The world of customer data management is changing and we believe the future lies in decentralized frameworks of data pools, exchange services and application environments. Today’s business landscape is becoming increasingly interconnected. Companies are connecting to and sharing data with an increasing number of stakeholders — customers, partners, vendors, subcontractors.

Existing data management solutions are no longer fit to meet these demands. Most of the top CRM and CDP platforms are monolithic solutions, architected many years ago. They struggle to meet the rapidly evolving needs of today’s businesses. Modern companies require a high degree of flexibility, interoperability, speed, and customization.

These silos today hold up to 80% of corporate data. Companies waste resources in moving, aggregating, cleansing, verifying and sharing data with other business entities and stakeholders. These walled gardens are fragmented and incomplete, slow and costly to access and prone to bias and censorship inherent in centralized systems. The consequence is considerable transactional friction leading to high barriers for efficient business interaction, compliance issues, as well as expensive migrations.

Stakeholders in this ecosystem want to finally unshackle from the dependencies that force them to hand over their data to the likes of Google, Facebook, SAP or Salesforce and pay big money to the likes of Accenture to implement CRM and data management solutions that still don’t get the job done. These complex and expensive implementations fail to provide an optimal level of usability and agility. Unencumbered access to data is essential to serving customers and markets. It is required for making decisions that maximize ROI and optimally drive growth.

The new decentralized enterprise data solutions being proposed, such as Cere’s Decentralized Data Cloud (Cere DDC) discussed in the following case study, will provide businesses, developers and data providers with a level playing field to build better experiences for their customers and target their audiences, leveraging real-time data through peer-to-peer collaboration with partners — businesses, data services vendors, developers and data scientists — within the Cere DDC.

Businesses want an easy way to securely share customer data between multiple applications and partners, the ability to track each unique customer journey in an omnichannel view, and share that data with on-demand business intelligence experts, data scientists, and data service vendors, to help better understand the users.

Application users want to control what kind of personal information, behavioral patterns, and transactional data they are willing to let applications collect and track in exchange for utility. Developers, on the other hand, want to build on top of an open-sourced, decentralized data cloud, with solutions that are not tied to walled-garden data silos such as Salesforce, Microsoft or SAP.

Case Study: Cere Decentralized Data Cloud

Taking the enterprise data revolution to the next step, Cere Network DDC has been building for the hyperconnected economy, where the blockchain six pack has been driving unprecedented interest from enterprises, especially as it pertains to transactions, data storage, and industry value chains/revenue models:

  1. Distributed shared data over peer-to-peer (P2P) networks reduces single points of failure;
  2. Consensus-driven trust cuts out the middle-man;
  3. Immutable transactions ensure trust;
  4. Hashing-based data ensures integrity and security;
  5. Automated smart contracts promote touchless interactions across process chains; and
  6. Permissioned and permissionless flavors give enterprise users flexibility.

These six blockchain features are changing the way we think about business transactions, data storage, and even industry value chains and associated revenue models. It is clear that the trend toward enterprise blockchain adoption is a cross-industry global phenomenon. Banking and financial services were the first mover from an enterprise blockchain adoption perspective accounting for 35%+ engagements, but other industries including supply chain, and other industry specific use cases are catching up fast.

Cere DDC is uniquely positioned to leverage blockchain technology, and further innovate within the enterprise data space, and bridge the vast amount of enterprise consumer data and use cases into the decentralized realm through connecting enterprises to the network via its SaaS operations and the Cere Data Science marketplace.

What Does Cere DDC Bring to the Table?

Cere is a Decentralized Data Cloud (DDC) platform backed by Binance Labs. Its cross-chain compatibility with networks like Binance Smart Chain, Polkadot, Cosmos, Ethereum and others bring Cere in a unique position to bridge the biggest enterprise companies with the fastest-growing decentralized ecosystems.

Cere DDC is advancing the area of innovation that has been spearheaded by Snowflake, which has just completed the biggest software IPO in history, indicating the market demand for innovative data solutions that can bolster this generation of business digitization. Based on a recent EY report, the key areas that will drive enterprise innovation beyond what companies like Snowflake have accomplished already will be reliant on blockchain technology. Cere built the natural evolution of the ‘next-gen’ snowflake due to benefits such as more efficient collaboration, better data agility, smarter integrations, more privacy, and ownership to users.

With pilot partners spanning hospitality, entertainment, and consumer goods industries, Cere’s Decentralized Data Cloud (DDC) platform is driving the adoption of a more ethical, agile, and interoperable process for managing customer data. Cere’s cross-chain compatibility with all major blockchains puts Cere in a unique position to bridge enterprise companies with the fastest-growing decentralized ecosystems.

To usher in a new era of customer data interoperability and data agility, the Cere DDC has been purpose-built with customer data privacy and anonymization from the ground up. Cere DDC provides a secure foundation for the next generation of customer cloud data solutions to cleanly abstract PII and fully encrypt individual data for both privacy compliance and near real-time personalization.

While initially set out to build a next generation CRM solution to break the “walled garden” created by companies like Salesforce, the Cere team saw a much bigger opportunity in the data cloud platform while working with Fortune 1000 pilot customers to build a viable decentralized alternative to Snowflake.

Ecosystem

There are multiple ways that Cere DDC participants and third-parties can participate in the Cere ecosystem. First, they can take part in the distributed systems, namely validating the blockchain and storing IPFS data. Second, they can create new services to perform new functions in instances. Finally, they can run an instance on behalf of others in a SaaS model. Each participant can either deploy a complete or partial instance on his own infrastructure as a sidechain, or rely on a trusted service provider of his choice; running a node on the Cere public network itself is also an option.

The Cere DDC is a self-sustaining open source based initiative. Initially Cere and its partners will be powering the Data Nodes and Validation Nodes to power this network, but the ecosystem will open up to other entities to join and start earning fees later in the roadmap, with the aim of achieving true decentralization.

Cere DDC Governance Principles

Data governance on Cere DDC is governed by the following four principles:

  1. Data Ownership

Customer data stored on Cere Chain is fully encrypted through secure RSA encryption, and partitioned per enterprise entity with a state of the art identity management system. Application data is associated with anonymous, randomized ID’s, non-identifiable personal information. Only users and entities with the associated private key can decrypt and deanonymize their own data.

2. Secure Collaboration

Cere will natively implement multi-party computing techniques such as federated learning and differential privacy to allow decentralized collaboration without exposing privacy regulated customer data to the party analyzing (part of) the data.

3. Regulatory Compliance

Companies operating in regions with strict data privacy regulations such as GDPR and CCPA can leverage Cere’s hybrid architecture to create a permissioned environment with blockchain-based authorization and audit capabilities defined by state transition functions, while still maintaining interoperability with the rest of the network.

4. Balance of Powers

The Cere Foundation positions itself as the mediator between enterprise interests and Cere community interests and ensures that potential conflicts and competing interests are resolved in a balanced and sustainable fashion.

Conclusion

The enterprise data sector is poised to see further innovation and disruption within the coming years. We believe decentralized data solutions such as Cere DDC are the missing link that businesses need, providing fully integrated solutions, packaged similarly to the SaaS platforms that they are already using and deployed to bring immediate efficiency improvements and cost savings to core business units.

Decentralized enterprise data platforms like Cere DDC represent the natural next step in the enterprise data SaaS revolution and are uniquely positioned to play a crucial role in bringing the vast markets of enterprise data into the future of trustless and interconnected web of decentralized networks.