Mar 20
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Overview of the event

Data lakes are storage repositories with an analytics and action purpose. You can see a data lake indeed a bit like a lake, without the swans and the water. ... But you get the idea: a big data lake in essence is a storage repository containing loads of data in their raw, native format. Data lakes typically require much larger storage capacity than data warehouses.Data lakes are next-generation hybrid data management solutions that can meet big data challenges and drive new levels of real-time analytics.

Data lakes can help break down silos, enabling organizations to gain 360-degree views of information and conduct cross-department, office or regional analytics. They also enable adoption of modern technologies such as artificial intelligence (AI) and the Internet of Things.

At Big Data Lake Summit, Hyderabad will bring together industry professionals and thought leaders from the field of Data Visualisation and Data Analytics to address the big data, data analytics etc questions and share best-practices in both a business-focused perspective and in a technical perspective. It will help you in understanding and implementing data visualization in your business/for your client. It will also provide an excellent opportunity to interact and network with some of the top minds.

Facts & Figures About The Event

7 Speakers
7 Topics
50 Tickets

Conference Schedule

Data Lake & Analytics Day, Bangalore
X Topic Abstract

A modern data warehouse lets you bring together all your data at any scale easily and to get insights through analytical dashboards, operational reports or advanced analytics for all your users. Modern Data warehouse enables to

• Combine all your structured, unstructured and semi-structured data (logs, files and media) using Azure Data Factory to Azure Blob Storage.

• Leverage data in Azure Blob Storage to perform scalable analytics with Azure Databricks and achieve cleansed and transformed data

• Cleansed and transformed data can be moved to Azure SQL Data Warehouse to combine with existing structured data, creating one hub for all your data. Leverage native connectors between Azure Databricks and Azure SQL Data Warehouse to access and move data at scale.

• Build operational reports and analytical dashboards on top of Azure Data Warehouse to derive insights from the data and use Azure Analysis Services to serve thousands of end users.

• Run ad hoc queries directly on data within Azure Databricks.

Speaker's Profile

Data and AI Architect having strong experience in Architecting and implementing Big Data Analytics enterprise solutions.

X Topic Abstract

As most organizations face challenges of Digitally Transformation, Dell's Data Lake Strategy and adoption/implementation has provided impetus to transform and modernize key business functions. One of such success stories is Digitally Transforming the entire Dell's Marketing and Supply Chain Fulfillment function.

Digital Supply Chain (DSC):All of the key supply chain functions, from plan to source to build to deliver are now Data empowered. What this means is that we have the right parts at the right time or making the right commitments to the various channels (, IVR, email etc.,). These decisions are driven by intelligent insights and inputs distilled from myriad of touch points and historical experiences using various analytical and learnt models with Data Lake at the epicenter.

PINE:Historically Dell relied on partners for Marketing and faced typical "Big Data" challenge of trying to handle multiple vendors, customer databases spread across various geographies. With Data Lake at the very heart, Dell Marketing functions were able to standup a high-quality global data system for all types of users. It also led to data rich modelling and customer intelligence for targeted and fruitful customer marketing engagements. In current state most of the Dell's B2B and customer marketing vehicles are fueled by oil(data) from Data Lake.

X Topic Abstract

Data lakes have opened up significant opportunities across multiple industries to deliver business outcomes in a cost effective manner. The sheer volume, velocity and variety of data opens up new business case opportunities that can help improve efficiency and enhance customer service. The reducing costs of bandwidth and IOT devices combined with increase in computer processing power has made it economical to put in-place a structured approach in formulating the nuts and bolts of having an optimal data lake strategy. In many consumer facing industries, the maturity of adoption is already high. On the other hand, in monopolistic industries like power and core infrastructure as well, a differentiated data lake strategy can deliver positive outcomes and contribute towards sustainable value. In particular, global challenges like climate change and environment can be better handled with big data tools that help integrate more renewable energy and contribute towards reduction in the global carbon footprint.

X Topic Abstract

With the competitive landscape of banks and financial services and digitization being imperative for all the banks, fraud management has its own challenges. In today's world banks have to be fast mover and ensure that they live up to the challenges of faster movement of money around them. This makes it all the more important for banks to deploy analytics model which would catch a fraudulent transaction even before it can take place. Few of the banks are moving ahead in that direction to ensure they do not end up losing stakelholder's money. Fraud Management is also moving beyond just monetary aspect within bank and moving towards a larger set up of assets including data.

X Topic Abstract

Majority of clients are taking steps to become analytics driven organizations - In their journey, key challenges that clients are facing are providing users access to all available data, increasing user adoption of data available with organizations, enable collaboration between users. Once clients create Data Lake and move all the data into Data lakes, challenge that clients will have is how do they ensure data from data lakes is used for creating analytical use cases. This session introduces new concepts that can be used to address this challenge

Speaker Profile

Murali is a business leader responsible for creating new service offerings around Data Monetization, Data Marketplaces in Data and Analytics practice for Global clients with responsibility for operational P&L. Murali is hands-on leader with diversified experience in creating New Service Offerings/Solutions from Concept to Market, creating New Practice scratch, Large Transformation Program Management, Global Delivery Management, Solution Architecture, Consulting for Fortune 100 customers.

Murali has delivered Outstanding 2X-3X growth in Practice with Intensive Execution of Strategy. Murali has 360 Degree View of Data and Analytics Practice Management experience for Insurance, Healthcare, Financial Services and Telecom clients.

Leading from front, new Solutions/Product development from Concept to Market, creating new Service Offerings to set up new practice from grounds up, Consult clients to solve business problems, Strategic planning, Customer Management, Account Management, delivery management, transformation program management, , Operations Management and Employee Engagement are his key traits. Murali is currently incubating Data & Insights Marketplace Practice to help clients to monetizing their Data and create new revenue streams. He has conceptualized & developed new Solutions around "Data & Insights Marketplace" that helps clients to set up Internal Marketplace, Buy-side Marketplace and Insights Marketplaces

X Topic Abstract

Data lakes Implementation and data management challenges.
• Review the state-of-the-art in data management for data lakes. We consider how data lakes facilitates solutions to classic problems including data extraction, data cleaning, data integration, and data versioning.
• The technology landscape and data lake Strategy (Hybrid Data Lake).
• Focus on the exciting new challenges that data lakes are inspiring.
• Deriving data insights and Machine learning for Executive decision making and strategic direction.

Speaker Profile

Nagaraju Kendyala is an accomplished result-oriented AWS Solution Architect and Enterprise BI Analyst with over 15 years of demonstrated experience in driving end to end implementation and timely delivery of high revenue projects across domains.
A passionate technology manager with expertise in cross-functional ERP implementations, delivery of high-impact data-driven business integrated analytics solutions, Product design, Cybersecurity risk reporting, Master data management and SOA Integrations.
He is an ardent coach and corporate trainer for Oracle Application Technical Stack and AWS Cloud. He loves exploring state-of-the-art technology solutions and enjoys mentoring young aspirants in AWS and ERP domain by working with them closely using learning by doing pedagogy.

X Topic Abstract

This session aims to give an insight into how Big Data analytics plays a pivotal role in Digital Transformation journey with real life examples of how such technologies can be used to transform factories into becoming a smart & connected factory. The session will discuss on specific aspects of non-functional requirements and the big data analytics architecture elements that are critical to realizing the objectives of the transformation journey, enabling factories to optimizing existing business processes and helping organizations staying ahead of the competition.

X Topic Abstract

Distributed Tracing System(Zipkin) gathers timing data needed to troubleshoot latency problems in service architectures. It will help us to detect and diagnose complex application performance problems.In this talk, we will explore all the approaches we have taken to collect and lookup of this data.

X Topic Abstract

Operationalization of Machine Learning models to production remains a challenge in the industry. This session aims to provide an approach to operationalize machine learning model as a REST API. The solution involves deployment of Python code as rest API to be consumed from any application. Application could be based on Azure function, .Net application , Logic apps etc. Also it is different from azure machine learning services because it gives us freedom to configure AKS cluster and nodes based on the requirement. Docker image libraries, configuration, app route, are configurable.

Speaker Profile

Data and AI consultant having strong experience in developing and architect enterprise solutions using Microsoft and Open Source products and Services.

X Topic Abstract

Identifying products a specific customer likes most can significantly increase the earnings of a company. For that purpose, a neural network classifier is used as a data-driven, visually-aware feature extractor. The latter then serves as input for similarity-based recommendations using a ranking algorithm.
Combined with more traditional content-based recommendation systems, image-based recommendations can help to increase robustness and performance, for example, by better matching a particular customer style. In this demo session, we will learn to build content-based recommender systems using image data.
Demo Session is divided into Five Major sections:
Section 1: Understanding of Recommender Systems (5 minutes)

· Collaborative Systems.
· Content-Based Recommender Systems.
Section 2: Deep Learning Algorithms for Unsupervised Computer Vision (10 mins)
· Convolutional Neural Networks (Convolution, MaxPooling, BatchNorm)
· Transfer Learning for CNN Architectures
o Inception Models
o RESNET Models
o VGG Models
Section 3: Understanding Similarity Measures (5 minutes)
· Euclidean Distance measures
· Cosine Similarity measures
Section 4: Building an End to End Content-Based Recommender System (20 minutes)
· Image and Data Preprocessing techniques
· Creating a Deep Learning model.
· Apply Hyperparameter tuning to improve model accuracy
· Create a Flask based Web App for showcasing Shirts.
· Running the end to end demo. Section 5: Question and Answers (5 Minutes)

Speaker's Profile

Sitaram Tadepalli works as Data Scientist with Tata Consultancy Servicesand has over 13 years of experience in solution designing, customer relationship and competency development.
He is researching the implications of emerging technologies such as Big Data and Analytics, Machine Learningand artificial intelligence on business models. He is working in corporate research and development division exploring initiatives on employee experiences, platform models, conversational systems, crowdsourcing, and innovation ecosystems.
Sitaram is a member of IEEE and Life member of Cloud Computing Innovation council of India. He is acting asSecretary and Treasurerfor Technology, Engineering and Management Society, IEEE Hyderabad Section.
He has published a couple of research papers in National and International conferences in the area of Big Data Analytics and Internet of Things and a patent on “Method and System Providing Analytics Platform for deriving Enterprise Collaboration Metrics”
Sitaram holds a Bachelor degree in Electrical and ElectronicsEngineering from Jawaharlal Nehru Technological University, Hyderabad and Master’s degree in Data Analytics from Birla Institute of Technology and Sciences, Pilani, India

X Topic Abstract

Now a days, we need to capture and store a wide variety of data types, and be able to access and analyze it when needed. The combination of technologies needed to do that is what we call a Data Lake, and it allows organizations to build new applications, new products and new business models that will redefine their business.

Data lake has ability to store structured data,unstructured data and raw data. Benefits include scalability,versatility,schema flexibility etc

Speaker Profile

Srinivas Jasti is working as a Senior Technical Manager in HCL with 15 years of demonstrated experience in driving development, support and transformation projects from monolithic to micro-service based architecture in Cloud. He has worked for enterprise companies like Capgemini, Tech Mahindra and IBM.

X Topic Abstract

Cloud based big data is the buzz in the industry. Companies are already using or implementing Data lake solutions that can scale at the pace of the cloud ,remove integration fences and enable a more data driven decision making for their organizations, at scale. As more data is generated in these solutions, arises the need to build a data governance model, because poor data management can result in lost transactions, inconsistent customer service, lost customers’ trust, and ultimately impact top line revenue.

This session looks at how a security and governance structure can be adopted with a look at best practices shared from the industry, with the data landscape in focus. We look at the tenets that can be adopted to establish a data lake platform, how to avoid a data swamp, thereby ensuring that self service analytics can be safely adopted at an enterprise level.

Speaker Profile

Snehith Allamraju is a Business Intelligence and Analytics Manager at Nobel Biocare. He has over 12 years of experience in the data and analytics domain, working on architecting, solution designing as well as program management. He is a certified SAP consultant in BW and BO, Tableau certified associate and an Azure certified Data Scientist.

He loves working and contributing with the local community to showcase Data and analytics tools and strategies. He is the Hyderabad Ambassador for the Open Data Science Conference (ODSC) meetup and part of the organizing team for the Hyderabad Tableau User group.

He dwells at the confluence of data, technology, design and strategy

Snehith holds a bachelor’s degree in Electronics and Communications Engineering from Jawaharlal Nehru Technological University, Hyderabad and master’s equivalent degree in Business Analytics from the Indian School of Business, Hyderabad.

X Topic Abstract

With the scale of growth of the Digital Data, we are in reality experiencing data deluge. No organisation will be able to sustain or become successful without having a solid data driven decision making system. To support the growing needs of organisation, an enormous amount of data to be processed to derive useful insights. Data in its raw form is not well suited for analytics and that is where Feature Engineering (FE) comes to the rescue. FE is defined as a process of creating Features representing underlying data objects. These features then play a pivotal role simplifying data engineering efforts in developing the holistic analytics solution .

At Salesforce, we analyse Petabytes of raw application log data everyday to drive product adoption, customer engagement, customer satisfaction and also reducing customer churn. To achieve this data driven decision making, a Feature Engineering(FE) process is developed facilitating automated metrics generation of 2K+ features at scale. In this talk session, we aim to share FE design approach which includes processes like New Feature Creation, Feature Transformation, Automated Metric Generation for features along with information on backfill process and data management activity involved.,

Our Sponsors

Use this opportunity to improve the visibility of your organization

Instant Sponsorship
Avail instant sponsorship at just USD 2000

Instant sponsorship includes
• Branding of your company as Bronze Sponsor – Company's Logo on the event page with cross link to your website.
• One Speaking Slot (45 min -non sales talk).
• 10% discount on registration fee for any delegate from your organization.
• Full day attendance at the event with lunch
• 1 x Roll up stand / Brochure distribution at the event
• Online Interview post of your company's senior executive at our media portal

For Silver, Gold Platinum & Titanium Sponsorship opportunites, please request for Sponsorship Brochure via email at,

Our Sponsors

Media Partners


Digital Marketing Partner

Marketing Partner

Promotional & Media Partners


Our Past Sponsors

Media Partner


Our Speakers

Nagaraju Kendyala

Enterprise/Cloud Solution Architect

Enterprise/Cloud Solution Architect

Ajit Kumar Thakur

consultant II(Data and AI)


Veerendra Thati

Big Data Analytics Architect


Nagaraju Chikoti

Practice Head, Manufacturing Analytics

Wipro technologies

Murali Prasad Patnala

Practice Lead, Data Marketplace Practice



IT Director


Gurudatta Kamath

Practice Head of Data and Analytics

Tech Mahindra

Sitaram Tadepalli

Data scientist


Uday Kiran



Manoj Chiruvella

Principle QA Analyst


Snehith Allamraju

Manager, Business Intelligence

Nobel Biocare India Pvt Ltd

Srinivasa Rao Jasti

Senior Technical Manager



IT Architect


Anup Kumar Ray

Data Architect

Sales force

Want to become a speaker Please register here Register

Our Pricing

Group of three or more(Early Bird)

Rs 7,500 + GST

Till 31st January, 2020
Group of three or more(Standard)

Rs 8,000 + GST

Till 20th March, 2020
Individual(Early Bird)

Rs 9,000 + GST

Till 31st January, 2020
Individual (Standard)

Rs 10,000 + GST

Till 20th March, 2020


Our Testimonial


Who can attend Data Lake & Analytics Day in Hyderabad?

CEOs, NGOs, developers, and anyone passionate about an accessible, game-changing technologies, modern business, including executives, inventors, strategies, marketers, visionaries, and creative minds from technology, business, and design, technical leads, architects, engineering directors, and project managers who influence innovation in their teams, all who want to learn from tooling to skilling and from strategies to fundamental values. Anyone working with data management, big data, analytics and business intelligence projects either on the business side or the technical side will benefit from attending this conference. And also, If your responsibilities include any of the below, you must attend:

• Predictive Analytics - Business Intelligence
• Data Visualization - Insight
• Data Science - Data Mining
• Software Engineering - Computer Science
• Data Journalism - Storytelling
• UX/UI Design - Graphic Design

Why to attend Data Lake & Analytics Day in Hyderabad?

From tooling to skilling and from strategies to fundamental values what needs to change and how? What are solutions and services available in market which I can leverage? Big Visualization Day 2017 is an attempt to seek and share answers to these basic questions.

What will you learn about?

Learn latest techniques and skills required for Data Science & Analytics from industry stalwarts themselves. Latest trends, concepts, processes and tools to understand and acknowledge challenges in Data Analytics emerging technologies. Meet and network with fellow Data Science & Analytics experts from leading companies. Learn how to adapt and adopt these changes quickly and swiftly within a team and also across the enterprise.

Are there any prerequisites to attend this program?


Do I need to register for the event?

Yes, all conference attendees must register in advance to attend the event.