Revanth Periyasamy
Data has emerged as a critical asset that drives decision-making, innovation, and competitive advantage. However, managing vast amounts of data from diverse sources presents significant challenges for organizations. Traditional data management methods often fall short, leading to fragmented workflows, data silos, and limited accessibility. This is where the concept of the data cloud comes into play.
By leveraging a data cloud, businesses can break down data silos, ensure data accuracy, and gain deeper insights that drive strategic initiatives and operational efficiencies. In this comprehensive guide, we will explore the history of data clouds, how they work, the essential capabilities they must possess, and their impact on various industries.
We will also delve into how enterprises are solving critical problems with data clouds and what the future holds for this transformative technology. By understanding the full potential of data clouds, organizations can make informed decisions to harness the power of their data, streamline operations, and achieve long-term success.
A data cloud is a centralized, cloud-based data management system that unifies an organization’s data from various sources. It serves as a single repository, ingesting data from databases, applications, social media, and even Internet of Things (IoT) devices. Regardless of the data format (structured, semi-structured, or unstructured), a data cloud securely stores, processes, analyzes, and visualizes the information within a single platform.
Cloud based data storage empowers businesses to overcome these limitations and unlock the full potential of their data. Here’s how:
The need for a data cloud is underscored by a recent study conducted by Harvard Business Review, 63% of chief executives don’t believe their companies make good use of their analytics. This highlights the critical role a data cloud plays in bridging the gap between raw data and actionable insights.
The evolution of data cloud technology has transformed how businesses manage and leverage data. Understanding its history helps appreciate the innovations and advancements shaping the current landscape.
In the early days of computing, data management was primarily centralized within mainframe systems. These large, powerful computers stored and processed data for entire organizations. However, the limitations of mainframe systems, such as high costs and lack of flexibility, led to the development of more distributed approaches.
In the 1980s and 1990s, on-premises data warehousing became popular. Companies invested in hardware and software to create centralized repositories for their data. These data warehouses allowed for better data integration and analysis but required significant upfront investment and ongoing maintenance.
The early 2000s saw the rise of cloud computing, which revolutionized data storage and management. Cloud service providers like Amazon Web Services (AWS), Google Cloud, and Microsoft Azure offered scalable, cost-effective solutions for storing and processing data. This shift enabled organizations to move away from expensive on-premises infrastructure to more flexible, pay-as-you-go models.
Building on the foundation of cloud computing, data clouds emerged as comprehensive solutions for managing vast amounts of data from diverse sources. Data clouds combined the scalability of cloud infrastructure with advanced data processing, integration, and analytics capabilities. Companies like Snowflake, Google BigQuery, and Amazon Redshift led the way, providing platforms specifically designed for modern data needs.
Today, data clouds are essential for organizations seeking to harness the power of their data. Innovations in artificial intelligence (AI), machine learning (ML), and real-time data processing are further enhancing the capabilities of data clouds. Platforms like Peliqan Data Cloud are pushing the boundaries by offering all-in-one solutions that simplify data management and unlock valuable insights.
A data cloud operates by integrating data storage, processing, and analytics within a unified cloud environment. Below is a breakdown of its components and process:
| Component | Description |
|---|---|
| Data Ingestion | Aggregates data from various sources like apps, IoT devices, and databases for processing. Ensures raw data is securely collected and ready for use. |
| Data Storage | Holds structured, semi-structured, and unstructured data in scalable, cloud-based warehouses. Supports high-performance and secure storage. |
| Data Integration | Unifies diverse data formats into a cohesive structure for streamlined analysis. Bridges gaps between disconnected data sources. |
| Data Processing | Handles large-scale data computations in real-time or batch operations. Employs distributed systems for efficiency and speed. |
| Data Analytics | Enables advanced querying, reporting, and AI-driven insights. Provides tools to visualize and interpret data trends effectively. |
| Data Sharing | Facilitates secure data exchange between teams and organizations. Encourages collaboration while maintaining governance. |
Enterprises across various industries are leveraging data clouds to solve critical business challenges and drive innovation. Here are some real-world examples:
Data clouds help logistics companies streamline operations and optimize supply chains. For example, Heylog uses Peliqan Data Cloud to integrate data from TMS systems and capture live transport location information. This integration enhances visibility and improves communication across the supply chain.
In the real estate sector, data clouds enable better project management and customer communication. Ziggu uses Peliqan to capture and analyze sales and customer data, facilitating informed decision-making and improving customer-centric approaches.
Financial institutions rely on data clouds for improved reporting and compliance. Horsum uses Peliqan as a central data hub for accounting software connectivity, enabling automated reporting and enhanced financial visibility.
Data clouds transform data management in the hospitality industry. CIC Hotels leverages Peliqan to consolidate data from different hotel management systems, streamlining monthly board reports and ensuring accurate, timely information.
Data clouds support personalized care and innovation in healthcare. Skindr uses Peliqan to centralize marketing and app download data, providing valuable insights into customer acquisition and lifetime value.
To fully harness the power of their data, organizations need data clouds with the following essential capabilities:
| Capability | Description | Features |
|---|---|---|
| Seamless Data Ingestion | A robust data cloud should offer seamless data ingestion from diverse sources, including databases, applications, social media, and IoT devices. | Pre-built connectors and APIs simplify the data collection process, ensuring efficient data ingestion. |
| Scalable and Secure Data Storage | Data clouds must provide scalable storage solutions that can handle various data types. | Security features like encryption, access controls, and user authentication are crucial for protecting sensitive information. |
| Advanced Data Processing | Powerful data processing engines are essential for cleaning, transforming, and preparing data for analysis. | Support for ETL and ELT processes ensures optimal data quality and readiness for advanced analytics. |
| Comprehensive Data Integration | Data integration capabilities are crucial for creating a unified view of an organization’s data. | Resolving inconsistencies and discrepancies, ensuring that all users access the same accurate information. |
| Analytics and Visualization Tools | Data clouds should offer advanced analytics tools, including AI and ML capabilities, to uncover hidden patterns and predict trends. | Integration with visualization tools like Metabase and Power BI allows for the creation of interactive dashboards and reports. |
| Data Activation Features | Data activation features enable businesses to put their data to work by sending alerts, distributing reports, and pushing data into business applications. | Ensures that insights lead to actionable outcomes. |
Implementing a data cloud can revolutionize how businesses handle and leverage their data. Here are some key benefits:
A well-known player in the market, Salesforce Data Cloud focuses on breaking down data silos and ensuring data accuracy. However, Peliqan Data Cloud goes beyond these basic functionalities, offering advanced features such as seamless data ingestion with 250+ pre-built connectors, powerful data processing capabilities, and data activation features that allow you to put your data to work by sending alerts, distributing reports, and pushing data into business applications.
Microsoft’s analytics and data platform, Fabric, offers a comprehensive set of tools for data integration, management, and analysis. While powerful, Peliqan Data Cloud differentiates itself by providing a more user-friendly interface, extensive self-service BI capabilities, and the ability to connect with a wide range of third-party tools like Metabase and Power BI for data visualization and advanced analytics.
Known for its scalability and performance, Google BigQuery excels at handling massive datasets. However, Peliqan Data Cloud offers a more well-rounded solution that covers the entire data management lifecycle, from ingestion to activation, making it a better fit for businesses looking for an all-in-one platform.
AWS offers a suite of data cloud services, including Amazon Redshift for data warehousing and Amazon Athena for serverless querying. While powerful, these services can be complex to set up and manage. Peliqan Data Cloud, on the other hand, provides a more accessible and user-friendly platform that empowers users across the organization to leverage data without requiring extensive technical expertise.
Snowflake is a popular cloud-based data warehousing solution that offers scalability, performance, and ease of use. While Snowflake excels at data warehousing, Peliqan Data Cloud provides a more comprehensive solution that goes beyond data storage and includes advanced features for data integration, processing, analytics, and activation, making it a better fit for businesses seeking an end-to-end data management platform.
Oracle’s data cloud offering provides a suite of services for data integration, management, and analysis. While OCI Data Cloud is a robust platform, it may be more suitable for enterprises already invested in the Oracle ecosystem. Peliqan Data Cloud, on the other hand, offers a more flexible and vendor-agnostic solution that can easily integrate with a wide range of data sources and third-party tools, making it a better choice for businesses looking for a platform that can adapt to their unique needs and existing technology stack.
While these data cloud platforms have their strengths, Peliqan Data Cloud stands out by offering a more comprehensive, user-friendly, and cost-effective solution that addresses the unique challenges faced by businesses across industries. By consolidating multiple data management functions into a single platform and providing a flexible pricing model, Peliqan Data Cloud helps businesses save on costs and scale their usage based on their needs.
Peliqan Data Cloud is an all-in-one data management solution designed to empower businesses of all sizes to leverage their data for optimal decision-making and competitive advantage. With Peliqan, organizations can overcome the challenges of traditional data management and embark on a journey towards data-driven success.
Peliqan breaks down data silos and creates a single source of truth for the entire organization. By ingesting data from diverse sources, Peliqan ensures that everyone has access to the same accurate and up-to-date information. Peliqan comes with a built-in data warehouse, or you can use your existing DWH such as Snowflake, Redshift, Azure or BigQuery.
Peliqan simplifies the data integration process, effortlessly pulling information from various sources with the help of 250+ pre-built connectors and automatically formatting it for further analysis. This eliminates the complexity and time-consuming nature of manual data integration.
Peliqan’s data activation features allow you to put your data to work, such as by sending alerts, distributing reports, and pushing data into business applications.
Peliqan’s powerful processing engine enables you to clean, transform, and prepare your data for analysis. It supports various techniques, such as ETL (extract, transform, load) and ELT (extract, load, transform), ensuring optimal data quality. Peliqan also includes Trino, a federated query engine, that allows joining data from different sources.
Peliqan connects to any BI tool such as Metabase or Power BI, in order to visualize data and convert complex datasets into clear, actionable insights.
Peliqan Data Cloud is a comprehensive data management solution designed to help businesses of all sizes harness the power of their data. Here’s what sets Peliqan apart:
Data cloud platforms like Peliqan have become essential for businesses across various sectors, enabling them to harness the power of data and drive transformative results. Let’s explore how Peliqan has helped organizations in different industries achieve their data-driven goals.
In the logistics industry, data cloud platforms play a crucial role in streamlining operations, optimizing supply chains, and improving communication. Heylog, a SaaS software company providing communication solutions for the logistics industry, leverages Peliqan to build and monitor integrations with TMS systems, as well as capture and distribute live location information from transports.
Read more: https://peliqan.io/case-study-heylog/
With Peliqan’s white-label data platform, 15+ connections to TMS and communication platforms, data pipelines and writeback capabilities, Heylog has achieved seamless data integration, enhanced visibility, and improved operational efficiency.
Data cloud solutions are transforming the way real estate companies manage their projects, communicate with customers, and make informed decisions. Ziggu, a central communication platform for real estate projects, uses Peliqan for internal Revenue Operations, capturing all Sales and Customer data.
Additionally, Peliqan facilitates customer integrations to and from the Ziggu platform. By building a RevOps data warehouse, enabling RevOps connectivity, and managing customer integration flows, Ziggu has gained valuable insights into its revenue operations and enhanced its customer-centric approach, ultimately driving growth and success in the competitive real estate market.
Financial institutions and accounting firms rely on data cloud platforms to streamline their processes, improve reporting, and ensure compliance. Horsum, a company that supports organizations with the analysis and improvement of operational and finance processes, uses Peliqan as the central data hub for accounting software connectivity and multi-customer management. With Peliqan’s accounting data collection, PowerBI integration, and alerting and activation flows, Horsum has empowered its clients with improved financial visibility, automated reporting, and data-driven decision-making capabilities.
The hospitality industry generates vast amounts of data from various sources, making data cloud platforms essential for managing and analyzing this information. CIC Hotels, which manages over 40 hotels in the Nordics region, each operating independently and using different software systems, relies on Peliqan to consolidate data for monthly board reports.
Read more: https://peliqan.io/case-study-cic-hospitality/
By building a Finance data warehouse, integrating accounting and hotel ERP sources, performing SQL transformations, and enabling Google Sheet writeback, Peliqan has saved the group CFO countless hours of manual data consolidation and ensured accurate, timely reporting across the entire hotel portfolio.
Data cloud solutions are revolutionizing the healthcare industry, enabling providers to deliver personalized care, improve patient outcomes, and drive innovation. Skindr, a mobile app that connects consumers with dermatologists for remote advice, uses Peliqan to centralize marketing data from multiple tools and app download data from the Apple App Store and Google Play Store.
Read more: https://peliqan.io/case-study-skindr/
By combining and transforming the data in Peliqan and using Metabase for data visualization, Skindr has gained valuable insights into its marketing performance, customer acquisition, and lifetime value, allowing them to make data-driven decisions and improve their services.
The evolution of data cloud technology is reshaping the way B2B SaaS companies position themselves. Taking cues from Salesforce’s successful transformation into the leading customer data cloud, B2B SaaS providers now have the unique opportunity to become the authoritative data cloud in their respective industries.
This shift isn’t just about offering software solutions; it’s about becoming the central hub for industry-specific data, providing organizations with a comprehensive, single source of truth. Peliqan’s white-label solution allows companies to seamlessly create their own branded data cloud, eliminating the need for lengthy development timelines.
With the ability to offer a powerful, scalable data cloud in weeks instead of years, Peliqan helps companies become indispensable by centralizing and enhancing the value of their industry-specific data. The future belongs to those who can transition from point solutions to comprehensive data clouds, and with Peliqan, that future is within reach. Ready to transform your SaaS platform into a game-changing data cloud? Contact us today to learn how you can make this transformation happen.
Revanth Periyasamy is a process-driven marketing leader with over 5+ years of full-funnel expertise. As Peliqan's Senior Marketing Manager, he spearheads martech, demand generation, product marketing, SEO, and branding initiatives. With a data-driven mindset and hands-on approach, Revanth consistently drives exceptional results.
Python ETL – What it is & top Python ETL tools Table of Contents Python ETL Made Simple Python has become the “de facto” language for ETL (Extract, Transform, Load) workflows due to its simplicity
Data Mesh 101 Table of Contents Data Mesh: What it is & how to implement it As organizations strive to become truly data-driven, they often struggle to find the right balance between business agility and
How CamelAI Leverages Peliqan for Unified SaaS Analytics Table of Contents Effortlessly Unify Your SaaS Data Many businesses struggle from having many disparate sources of data. Marketing tracks leads in HubSpot, sales monitors interactions in
CIC Hospitality saves 40+ hours per month by fully automating board reports. Their data is combined and unified from 50+ sources.
Heylog integrates TMS systems with real-time 2-way data sync. Heylog activates transport data using APIs, events and MQTT.
Globis SaaS ERP activates customer data to predict container arrivals using machine learning.
