Ankush

With over a decade of experience in data engineering, analytics, and artificial intelligence, you are a seasoned professional adept at managing complex data ecosystems and leveraging AI technologies. Your expertise spans across database management, data analysis, visualization, and AI applications, with proficiency in languages like Python and SQL, as well as advanced tools such as Spark, Snowflake, Hadoop, and various machine learning frameworks. As a Data Solutions Engineer at Vail Systems, you've demonstrated your ability to prototype data models, maintain data quality, and enable cloud technology adoption, while incorporating AI-driven insights into your solutions. Your track record includes developing robust ETL/ELT processes, optimizing data pipelines, and partnering with cross-functional teams to drive product improvements through data-driven and AI-enhanced approaches. Your work with speech and voice analytics data, as well as high-volume telephony systems, showcases your capability to handle diverse and complex datasets, applying artificial intelligence techniques for advanced pattern recognition and predictive modeling. With a proven history of increasing efficiency and reliability in data operations and implementing cutting-edge AI solutions, you bring a valuable blend of technical skills, AI expertise, and business acumen to any data-driven organization looking to harness the power of artificial intelligence.

SQLServerCentral Article

Designing SQL Server Pipelines That Are Ready for AI Before You Actually Need AI

Introduction. Why AI Readiness Starts in the Database You probably don’t need machine learning today. Most organizations don’t. You already have reporting dashboards, operational workflows, and business intelligence that work just fine without neural networks or predictive models. That’s not a failure. It’s normal. The problem doesn’t show up immediately. It shows up a few […]

(4)

You rated this post out of 5. Change rating

2026-02-27

1,927 reads

SQLServerCentral Article

JSON in Microsoft SQL Server: A Comprehensive Guide

Introduction JSON (JavaScript Object Notation) has become a popular data format for storing and exchanging information. Microsoft SQL Server, starting from version 2016, introduced built-in support for JSON, allowing developers to work with JSON data more efficiently within the relational database environment. This article will explore how to store, retrieve, and manipulate JSON data in […]

(10)

You rated this post out of 5. Change rating

2025-01-31

14,852 reads

Blogs

Monday Monitor Tips: AI Query Analysis

By

AI is everywhere. It’s in the news, it’s being added to every product, management...

AI: Blog a Day – Day 8: RAG – Retrieval Augmented Generation

By

RAG — Retrieval Augmented Generation. we have covered so far — embeddings, vectors, vector...

AI: Blog a Day – Day 7: Vector and Vector Databases

By

Continuing from Day 6 we learned Embeddings, Semantic Search and Checks, on Day 7...

Read the latest Blogs

Forums

I'm thinking about submitting some articles

By Doctor Who 2

I've written some documentation on using different Markdown types of files on GitHub. It's...

Not Just an Upgrade

By Steve Jones - SSC Editor

Comments posted to this topic are about the item Not Just an Upgrade

Restoring On Top I

By Steve Jones - SSC Editor

Comments posted to this topic are about the item Restoring On Top I

Visit the forum

Question of the Day

Restoring On Top I

I am doing development work on a database and want to keep a backup so I can reset my database. I make some changes and want to restore over top of my changes. When I run this code, what happens?

USE Master
BACKUP DATABASE DNRTest TO DISK = 'dnrtest.bak'
GO

USE DNRTest
GO
CREATE TABLE MyTest(myid INT)
GO
USE master
RESTORE DATABASE DNRTest FROM DISK = 'dnrtest.bak' WITH REPLACE

See possible answers