top of page
data-circle.png

BigQuery Deployment Specialists

data-undulation-grey-v2.jpg
google_bigquery-ar21.png

Kaleidoscope Data partners with businesses who leverage Google BigQuery as their preferred data warehousing platform.

We guide companies in BigQuery use, cater to their unique data needs, and help build their own data teams to boost in-house analytics capabilities.

Why Kaleidoscope?

  • We're skilled at navigating data migration challenges

  • We love unique use cases, such as geospatial analysis

  • We simplify working with numerous data sources

  • We handle things like query performance optimization so you can run your business

BLOG POST SNAPSHOT

"How can we improve multi-tenancy architecture in BigQuery?"

The existing multi-tenancy architecture in BigQuery requires writing data into each tenant dataset before performing transformations, which leads to inflexibility, time-intensive processes, and potential security risks.

Kaleidoscope Data created an alternative architecture using DBT for global transformations before separating the data into client datasets, aiming to address these drawbacks and provide easier scaling and improved analytics schema for clients.

sine-wave-data-points-diagonal.jpg

BigQuery + KALEIDOSCOPE DATA

Numerous Kaleidoscope Data clients opt for BigQuery owing to its powerful analytical capabilities, agile infrastructure compared to conventional data warehouses, and Google's commitment to security and innovation.

Our skill set extends across various BigQuery applications, from integrating machine learning models to implementing real-time analytics. We can even train your staff.

Typical BigQuery use cases:

ANALYTICS

  • Big data analytics

  • Real-time analytics

  • Deep historical analysis

  • Data sharing and collaboration

  • Predictive analytics

  • Data visualization

  • Text analytics

  • Sentiment analysis

  • Anomaly detection

  • Segmentation analysis

DATA ENGINEERING

  • Data warehousing

  • Data transformation

  • Data migration from SaaS applications

  • Real-time data streaming

  • Data integration

  • Data quality management

  • Data governance

  • ETL (Extract, Transform, Load) processes

  • Data cataloging and metadata management

MACHINE LEARNING

  • Building ML models on structured data

  • Operationalizing ML models

  • Predictive modelling

  • Customer behavior prediction

  • Sales forecasting

  • Natural Language Processing (NLP)

  • Image recognition

  • Recommender systems

  • Time series analysis

  • Fraud detection

sine-wave-data-points.jpg

CONCERNS THAT FALL UNDER
"YEA, WE'VE GOT YOUR BACK"

Integrating BigQuery with multiple data ecosystems (financial systems, marketing platforms, sales tools, etc.)


Handling diverse data schemas (standard SQL, nested and repeated data, etc.) within BigQuery

Setting up and managing scheduled queries and alert systems in BigQuery

Creating efficient, scalable, and future proof data models in BigQuery

 

Automating data quality checks in BigQuery

topographic-depth-map-teal.png
CONTACT US
arrow&v

Thanks for submitting!

Contact Us
bottom of page