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

2,010 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

15,010 reads

Blogs

Whiling away an afternoon, thinking

By

I come to Heathrow often. Today is likely somewhere close to 60 trips to...

Black Box vs. Gray Box vs. White Box Testing

By

If your organization is spending money, then meaningful results are a must. Pen testing...

Webinar Series – SQL Server Indexing

By

I’m starting a webinar series about SQL Server indexing with the fine folks of...

Read the latest Blogs

Forums

Restoring On Top II

By Steve Jones - SSC Editor

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

SQL Art 2: St Patrick’s Day in SSMS (Shamrock + Pint + Pixel Text)

By Terry Jago

Comments posted to this topic are about the item SQL Art 2: St Patrick’s...

Breaking Down Your Work

By Steve Jones - SSC Editor

Comments posted to this topic are about the item Breaking Down Your Work

Visit the forum

Question of the Day

Restoring On Top II

I have a database, DNRTest, that has a number of tables and other objects in it. The other day, I was trying to mock up a test and ran this code on the same server:

-- run yesterday
CREATE DATABASE DNRTest2
GO
USE DNRTest2
GO
CREATE TABLE NewTable (id INT)
GO
Today, I realize that I need a copy of DNRTest for another mockup, and I run this:
-- run today
USE Master
BACKUP DATABASE DNRTest TO DISK = 'dnrtest.bak'
GO
RESTORE DATABASE DNRTest2 FROM DISK = 'dnrtest.bak' WITH REPLACE
What happens?

See possible answers