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Cloud Data Analytics - Oct 18 2021

Web Chat Series #1: Financial Institutions Improve Business Outcomes With Data Transformation, Intelligent Automation and Innovation

San Mateo, CA | October 18 — Today’s discussion is the first of a 3-part web chat series on how financial services institutions are improving business outcomes leveraging data transformation, intelligent automation, and innovation.

(The following is a summary of a web chat between Bill Draper – a seasoned Silicon Valley executive, entrepreneur, and President of NextPhase.ai, and Sanjeev Mohan – Strategic Advisor to NextPhase.ai and former Vice President at Gartner.)

Why Is Data Observability Critical for Financial Services? 

Data observability is critical to provide banks with the ability to fully understand the health of the data in their system, while eliminating data downtime by applying best practices to data pipelines. It also provides a continuous and holistic view of the data landscape to deliver reliable analytics that enable an opportunity to optimize and fine tune data pipelines.

Due to the nature of the various systems used in financial services, there are typically many silos. This is further complicated by constant data replication and legacy ETL scripts, which can malfunction and cause major data breakage issues. A core component of data observability is having the ability to consolidate the data into a “Single Source of the Truth,” with the market momentum pivoting to data cloud platforms such as Snowflake to leverage the numerous benefits of a data cloud solution.

By building pipelines that have automation, advanced levels of orchestration with real-time monitoring, notification, and immediate remediation and response, this will greatly mitigate the prospect of major data linkage issues and data downtime.      

How Is Data Governance Related to Financial Institutions? 

In governance, two sets of compliance regulations are top of mind with most financial services organizations. While they are different in focus and impact, the financial services industry needs to adhere to both of them. The first is regional geographical regulation, and the second is more industry specific. 

Regional compliance is more well known, such as the EU, GDPR, and California CCPA, which all require a bank’s customers to have more control over their personal data that has been collected. With industry-specific compliance regulations, banks have PCI DSS, compliance requirements for credit cards, FISMA and SOX for regulatory requirements. As banks become more globalized, the issue of data residency becomes of greater concern.

Historically, banks were less concerned about where the data was being kept. However, with new regulations such as GDPR, which are global in nature, there are requirements to keep personal data within certain geographical regions. That means banks need to build modern architectures, which take into account all of these mandated compliance privacy regulations.

Why Are Financial Institutions Accelerating Their Transformation to the Cloud?

Some of the primary issues banks face are data accessibility and scalability. Some of the drivers of these constraints are data silos coupled with the limitations of on-premise architectures. This inhibits their ability to improve outcomes in two key customer sectors: 1) The customer experience, and 2) The customer 360 degree view. As a result of the changing landscape of governance, customer expectations, and the limitations of legacy on-premise data platforms, we see more banks moving to a single data cloud platform, such as Snowflake. This provides far greater data accessibility, scalability, and alignment with executing towards desired business outcomes. For banking customers, data transformation is enabled by leveraging modern technologies, such as the data cloud, and providing meaningful insights driving business growth and value.

Check back for our next web chat covering specific banking client examples of how a cloud data transformation is critical to the overall business strategy execution.

Have questions? We help companies like yours, every day.

Email us at hello@nextphase.ai

About NextPhase.ai

NextPhase.ai is a data cloud services provider specializing in Snowflake, cloud data management and analytics technologies. We accelerate enterprise digital transformation initiatives by leveraging our innovative cloud data management technology, “NextPhase.ai DATAFLO” to optimize and rationalize disparate enterprise data into relevant insights. “DATAFLO” is designed to automate the lifecycle of data management transformation using AI and ML along with expeditious on-ramps to the Snowflake data cloud infrastructure. NextPhase.ai provides a range of technology consulting services for the Financial Services, Biotech and Technology industry sectors combining our platform-based services, seasoned talent, and industry proven methodology so our customers can harness more from their data. We are a Silicon Valley based company with global presence having delivered high value service engagements for numerous Global 2000 enterprises.

 

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