Cloud computing and SaaS applications have transformed business processes. But the many APIs, databases, and new technologies make it very challenging for organizations to get a unified view of their customers and derive data-driven insights to inform accurate and timely decision-making.
The good news is that you don’t have to reinvent the wheel to overcome these hurdles. A Modern Data Stack Platform (MDSP) can set you up for success in today’s data-driven business environment. Here’s what you need to know.
Navigating the Modern Data Landscape is Challenging
You need to build an analytical framework before you can derive insights from data. But it’s easier said than done.
It’s complicated to load data from multiple sources and return results in a fraction of a second using legacy tools. Additionally, you have to write highly complex code to query data to gain meaningful insights. Yet, relying on manual reporting is no longer an option and the adoption of data literacy across the organization is no easy feat.
Engineering teams must solve many dependencies to move an organization toward analytical maturity. Building such a framework from scratch is labor-intensive, time-consuming, and costly. Moreover, businesses must ensure that technology requirements don’t become a bottleneck for growth while freeing up their engineering teams to focus on strategic initiatives.
Organizations need a solution that seamlessly integrates dispersed data sources, reduces engineering time, provides automated reporting, lowers the cost of analytics, provides easy hook-ins to clean data for data science, and delivers valuable business insights—a modern data stack.
What is a Modern Data Stack?
The modern data stack is a data integration platform with a cloud data lake and data warehouse supported by a collection of cloud-native tools. It gives you access to essential components to transform into a modern data-driven organization:
- An efficient ETL/ELT mechanism to unify data from multiple sources.
- A platform to create a single source of truth, enforce governance, and increase trust in data.
- A cloud-based solution that’s easy to scale, access, and maintain.
- Advanced data transformation tools to meet fast-evolving customer expectations and business needs.
- A robust data warehouse or data lake to meet storage and analytical requirements.
- A business intelligence tool for visualizing and communicating data insights.
The cloud-based subscription model (also known as PaaS, Platform as a Service) means you don’t have to invest in installation and maintenance.
Automation technologies allow you to operationalize data workflows and increase cost-efficiency. Meanwhile, you pay for what you use and have the flexibility to scale up at a moment’s notice, so you don’t have to spend on excess capacities you don’t need right away.
Can I Build a Do-It-Yourself (DIY) Modern Data Stack?
Theoretically, you can. But if you cobble together different tools, you may find yourself back in square one: juggling a collection of disjointed solutions that may or may not play nice with each other. You’d also likely spend a lot of time and resources playing catch up with fast-evolving business requirements and consumer expectations.
Integrating open-source tools for such a complex application is challenging—you may find your answer in the community forum, or you may not—not a good strategy when your critical business decisions are at stake.
Also, a DYI approach doesn’t give you a unified console to manage privacy, governance, security, and telemetry, which are essential requirements in today’s business and compliance environment.
What Does a Modern Data Stack Platform Look Like?
A Modern Data Stack Platform provides all the necessary infrastructure and technology support to help you productize your data and build a data-driven organization. It delivers a unified management experience by bringing various data processing capabilities under a security, privacy, and governance umbrella.
For example, SkyPoint’s Modern Data Stack Platform consists of the following components:
SkyPoint Dataflow: A no-code data ingestion and activation tool that builds reliable ELT and Reverse ETL data pipelines with 200+ connectors to integrate and manage large volumes of data from multiple sources.
SkyPoint Lakehouse: A unique analytical storage solution that combines the benefits of a data warehouse and data lake using Delta Lake technology and the Common Data Model.
SkyPoint Lakehouse SQL: An open data integration architecture that connects your data with anything that can understand SQL (i.e. Power Query, Power BI, and dbt).
SkyPoint Resolve: Our proprietary machine learning-based identity resolution algorithm produces rich, accurate, and precise 360-degree customer profiles to establish a single source of truth.
Skypoint Profile: Real-time customer profiles support personalized and trusted interactions across platforms while allowing you to view each customer’s journey as it evolves.
Skypoint Predict: AI-powered built-in and custom models help you anticipate customer needs with real-time data and deliver meaningful experiences across the entire customer journey.
SkyPoint Activate: Robust features to support granular audience segmentation, provide insights for meaningful 1:1 interactions at scale, and boost the ROI of your favorite marketing tools.
SkyPoint Automate: Seamless API integrations connect unified, trusted data with business applications to empower citizen developers and accelerate innovation—like Microsoft’s Power Platform or Teams.
SkyPoint Vault: A zero-trust storage solution that isolates, encrypts, stores, and governs sensitive data to help you build applications faster while staying compliant with various privacy laws.
SkyPoint Empower: An all-in-one automation solution that integrates consent and preference management with data residency and privacy protection to ensure compliance with GDPR, CCPA, and other state laws.
Connect the Data Dots With SkyPoint Cloud
SkyPoint Cloud’s Modern Data Stack Platform is a single product with a suite of AI-driven customer data tools to help you break down data silos, connect all your insights, and unify data processing to deliver a seamless, privacy-first customer experience.
We continuously evolve our technologies and open architecture to bring people and data together. We invite you to do the same by trying our platform.