Databricks Data + AI Summit 2026

Databricks Data + AI Summit 2026

 

June 15–18, 2026 | San Francisco + Virtual

TEK Analytics will be attending Databricks Data + AI Summit 2026, one of the leading global events for data, analytics, and AI. The summit brings together data leaders, engineers, scientists, architects, and business teams to explore the latest in data intelligence, governance, analytics, applications, agents, and AI.

At the event, our team will be connecting with organizations that are looking to modernize their data architecture, unlock more value from SAP data, and build a stronger foundation for AI.

Let’s connect at Data + AI Summit

Many enterprises are asking the same questions right now:

How do we bring SAP data into a modern lakehouse?
How do we integrate SAP and Databricks without creating more complexity?
How do we govern SAP-sourced data across platforms?
How do we build an AI-ready data foundation that can scale?

These are the conversations we will be having at Data + AI Summit.

Whether you are exploring SAP + Databricks integration, lakehouse architecture, Unity Catalog governance, AI use cases, or a broader data modernization roadmap, we would be happy to connect.

Meet with TEK Analytics

TEK Analytics brings dual-skilled expertise across SAP and Databricks, helping organizations connect governed SAP data with scalable analytics and AI platforms.

Our team will be available for informal 30-minute conversations around your priorities, challenges, and next steps.

No generic pitch. No heavy presentation. Just a practical discussion on what you are trying to solve and how to move forward with clarity.

 

Event Details

Event: Databricks Data + AI Summit 2026
Date: June 15–18, 2026
Location: San Francisco + Virtual
TEK Focus Areas: SAP + Databricks, Lakehouse Architecture, Unity Catalog Governance, AI-ready Data Foundations, Data Modernization
Event Website: Databricks Data + AI Summit 2026

Schedule Time with TEK:

SAP Sapphire & ASUG Annual Conference Orlando 2026

SAP Sapphire & ASUG Annual Conference Orlando 2026

 

May 11–13, 2026 | Orange County Convention Center, Orlando

TEK Analytics will be attending SAP Sapphire & ASUG Annual Conference Orlando 2026, SAP’s flagship event bringing together SAP leaders, industry experts, partners, and peers to explore the future of business, data, applications, and AI.

At Sapphire, our team will be connecting with SAP leaders and customers to discuss practical ways to modernize SAP data landscapes and prepare for the next generation of analytics and AI.

Let’s connect at SAP Sapphire

Many organizations are asking the same questions right now:

How do we modernize BW without unnecessary complexity?
How do we make SAC and S/4 planning work at scale?
How do we bring SAP data into a platform that is ready for AI?
How do SAP and Databricks fit into our future architecture?

These are the conversations we will be having in Orlando.

Whether you are planning a BW modernization journey, evaluating SAP Business Data Cloud, exploring Databricks integration, or looking to improve planning and analytics, we would be happy to connect.

Meet with TEK Analytics

Bharat Sunkari, CEO, and Phil King, VP of Strategy and Growth, will be onsite and available for informal 30-minute discussions.

No presentations. No generic pitch. Just a practical conversation around your priorities, challenges, and next steps.

Event Details

Event: SAP Sapphire & ASUG Annual Conference Orlando
Date: May 11–13, 2026
Location: Orange County Convention Center, Orlando
TEK Focus Areas: SAP BW Modernization, SAP Analytics Cloud, SAP Business Data Cloud, SAP + Databricks, AI-ready data architecture

Schedule Time with TEK:

Maximize Auto Parts fill rate with SAC Predictive reporting

About the Client: Fortune 100 Automotive Customer

The Fortune 100 Automotive Customer is one of the world’s largest and most important car manufacturers with 6 million market capture. It has 50 production locations across the five continents with 200000 employees across the globe. To be a leading, profitable volume manufacturer as well as playing a leading role in the new world of the automobility industry in the long term.

 

Business Challenge:

Maximizing the Dealer orders Fill percent or Fill Rate is always a key focus in the automotive after-sales stream. Increasing fill rate without piling excessive inventory at a plant requires not only a deep dive into fill rate and supply chain metrics across multiple dimensions but also deep learnings into data patterns and identify influencers impacting the fill rates.

 

The Solution:

A complete cloud-based reporting solution for tracking fill rate from Plant to the part level. Our consultants in partnership with the business developed a regression-based predictive model by taking the last 3 years’ dealer order history and fill rates into the account. The Model predicts future fill rates for the dealer odder demand data in the planning system.

  • Gather data from supply chain history for drilling, rigging, pipeline materials, other inputs, part failure, and part usage history, lead time history (for reorders), history of disruptions to supply chain, planned and the actual history of ramping of capacity.
  • Unified Historical and planning data along with master data within BW/4HANA
  • Reporting Model which enables multiple drill-down levels and secured at region leve
  • An easy-to-use yet very effective SAC-based visualization to track Fill rates historically and also drill down to material level with multiple end-user level capabilities including Ranking, Ad-hoc exploring.
  • Considering 3 years dealer order history, created a regression model which predicts fill rate and quantities at a part level for demand planning data
 

 

Results and Benefits:

  • The SAC story completely replaced excel based fill rate tracking. Users no longer need to perform any manual excel calculations to derive KPI’s which tremendously save time in analyzing.
  • A very user friendly yet robust UI design
  • A deeper insights into the fill rate data across multiple dimensions and
  • 95% confident regression model trained from 3 years historical data which predicts the future fill rates, this will help users to maintain optimal inventory

Get our case study