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Understanding Today’s ETL Pricing Landscape: Column vs Row Approaches
Most ETL pricing models haven’t kept pace with the evolving data landscape, leaving many teams overpaying for row-based processing that penalises growth and efficiency. This blog advocates for a shift toward performance-based pricing aligned with column-oriented processing, offering scalable, transparent cost control that reflects actual infrastructure usage rather than arbitrary metrics.
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Snowflake Columnar Storage: Why This Architecture Could Cut Your Analytics Costs by 70%
Snowflake’s columnar storage architecture delivers faster analytics and lower costs by scanning only relevant data, compressing storage intelligently, and optimising queries automatically. This design enables significant performance gains and cost reductions across ETL, storage, and compute—transforming how businesses scale data operations and consume insights.
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How Smart Data Teams Cut Costs Without Sacrificing Performance
This blog explores how data teams can strategically reduce costs without compromising performance, drawing insights from a recent LinkedIn Live featuring experts from Select.dev, Cube, and Matatika. It outlines five key strategies, from optimising human productivity to safely switching platforms, backed by real-world examples and practical implementation steps.
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From Tool Mastery to Systems Design: How Data Engineers Actually Grow
Many data engineers plateau after mastering tools but struggle to scale because they haven't learned to think in systems. This blog explores how transitioning from query writing to system design is the key to sustainable growth, effective mentorship, and resilient analytics platforms.
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Why Most SQL Server Data Tools Migrations Fail (And How to Build Better Ones
Many data teams avoid SQL Server Data Tools (SSDT) migrations due to cost, complexity, and risk, leaving them stuck with outdated systems and growing technical debt. Matatika’s Mirror Mode offers a safer, more cost-efficient alternative by enabling secure, isolated testing environments that mirror production without exposing sensitive data or inflating infrastructure costs.
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