Remove Datasets Remove Raw Data Remove Structured Data
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Simplifying BI pipelines with Snowflake dynamic tables

ThoughtSpot

When created, Snowflake materializes query results into a persistent table structure that refreshes whenever underlying data changes. These tables provide a centralized location to host both your raw data and transformed datasets optimized for AI-powered analytics with ThoughtSpot.

BI 111
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From Schemaless Ingest to Smart Schema: Enabling SQL on Raw Data

Rockset

You have complex, semi-structured data—nested JSON or XML, for instance, containing mixed types, sparse fields, and null values. It's messy, you don't understand how it's structured, and new fields appear every so often. Without a known schema, it would be difficult to adequately frame the questions you want to ask of the data.

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Microsoft Fabric vs Power BI: Key Differences & Which to Use

Edureka

Microsoft offers a leading solution for business intelligence (BI) and data visualization through this platform. It empowers users to build dynamic dashboards and reports, transforming raw data into actionable insights. However, it leans more toward transforming and presenting cleaned data rather than processing raw datasets.

BI 40
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What is Data Enrichment? Best Practices and Use Cases

Precisely

According to the 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, 77% of data and analytics professionals say data-driven decision-making is the top goal of their data programs. That’s where data enrichment comes in.

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A Guide to Data Pipelines (And How to Design One From Scratch)

Striim

Third-Party Data: External data sources that your company does not collect directly but integrates to enhance insights or support decision-making. These data sources serve as the starting point for the pipeline, providing the raw data that will be ingested, processed, and analyzed.

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How to Become a Data Engineer in 2024?

Knowledge Hut

If we look at history, the data that was generated earlier was primarily structured and small in its outlook. A simple usage of Business Intelligence (BI) would be enough to analyze such datasets. However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured.

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Understanding Dataform Terminologies And Authentication Flow

Towards Data Science

Dataform enables the application of software engineering best practices such as testing, environments, version control, dependencies management, orchestration and automated documentation to data pipelines. This means dataset and tables generated from development workspace are manifested within the staging environment.