Modern Data Stack
Modernizing the Data Stack
As data becomes more complex, organizations are on the lookout for swifter, more efficient, and cost-effective methods to handle and scrutinize it. Over the past few years, cloud-based data warehouses have altered data processing with their cutting-edge massively parallel processing abilities and SQL support. This advancement has paved the way for a range of cloud-native data tools that are user-friendly, adaptable, and budget-friendly.
SME's Modern Data Stack includes a collection of tools and technologies built for the cloud, revolutionizing how enterprises tackle data management.
Transform Your Data Management and Analysis with Comprehensive Modern Data Stack Solutions
We provide a comprehensive suite of modern data stack tools and professional services to help organizations transform their data management and analysis capabilities. Our cloud-based tools enable organizations to collect, integrate, warehouse, transform, and consume data more efficiently and accurately than traditional stacks, while our team of experienced professionals provide expert guidance and support to ensure successful implementation and adoption. Whether you're just starting out or looking to upgrade your existing data infrastructure, we have the tools and expertise to help you achieve your data goals.
Modern vs Traditional Data Stacks
The traditional data stack refers to on-premises hardware, relational databases, ETL tools, and BI software. The modern data stack utilizes cloud-based data warehouses, integration and transformation tools, and modern BI and visualization tools. Modern stacks can handle larger volumes of data and integrate data in real-time, providing a more agile and cost-effective solution for data management and analysis.
From Manual to Automated
The modern data stack automates data collection using cloud-based tools to connect to various sources and pull data into a central location in near real-time. This approach provides a more efficient and accurate way to collect and transform data compared to traditional data stacks, which often involve manual processes and separate tools for data integration and transformation.
Cloud-Based Integration for Real-Time Data Handling
The modern data stack uses cloud-based integration tools to handle large volumes of data from various sources in real-time. It also allows for the integration of cloud-based sources that may not have been accessible in the traditional stack, providing a more flexible and efficient approach to data integration.
Flexible and Cost-Effective
The modern data stack uses cloud-based data warehouses that are more scalable, flexible, and cost-effective than the traditional stack's on-premises hardware. Cloud-based data warehouses also offer advanced analytics capabilities, providing a more efficient way to store, process, and analyze data.
Extract, Load, Transform
The modern data stack's cloud-based data transformation tools utilize the ELT paradigm to push the processing duties to the cloud data warehouse. These transformations can be accomplished via no-code/low-code workflows that provide a more user-friendly interface for faster data transformation or modularized SQL/Python that gives advanced data engineers more control. They also offer built-in data validation and lineage tracking to ensure data quality and traceability. This is in contrast to the traditional data stack, where data transformations are typically done inside legacy ETL tools which require more hardware and therefore cost more.
Democratizing Data Insights
The modern data stack allows for self-service data consumption through user-friendly, cloud-based data visualization and reporting tools that democratize access to data insights. Traditional stacks typically limit data consumption to a select group of data experts who use specialized tools.
Self-Service Discovery of Trusted Data Assets
The modern data stack integrates data governance tools with other components, providing a more comprehensive view of data across the organization. Advanced analytics capabilities detect and prevent data quality issues before they impact business operations, ensuring consistent data access, security, and compliance.
Building long-lasting relationships through happy customers.
BUILDING USER CONFIDENCE WHILE REDUCING CLOUD COMPUTING COSTS
Kforce migrated from costly, legacy ETL processes to a modern approach that has widespread positive impacts on the business.
MINI-EPISODES TO HELP POWER BI USERS GO FROM KNOW TO PRO
Starts with the basics of what you need to know about PBI Desktop, an overview, and importing some data within the Power Query Editor.
DIGITAL TRANSFORMATION AND AI IMPLEMENTATION
Ideal Agent is partnering with SME to scale the business, reduce overhead expenses and improve customer experience.
MODERN CLOUD DATA WAREHOUSES TO THE RESCUE
Big data is becoming more diverse, distributed, and dynamic. This strains your data warehouse and existing BI processes.