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, Hyderabad
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

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

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

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

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.,

X Topic Abstract

Traditionally, enterprises have been using AI or any data-driven approach for business decisions and marketing and everyone believes that AI is the way forward.

Verizon has taken an approach to integrate AI while also redesigning the customer journey so that customers have the best experience with us when they engage.

The thought process is about enabling AI in the business process by having a strong decision management framework converting the machine learning assets into business decisions.

When we talk about decisions influenced by AI, it's also critical to look at the biases and how we should take care of that. We will cover the types of biases and what Verizon has been doing and the path forward.

X Topic Abstract

AI-driven automation reconfigures ideas, interests, influence, and investments in the AI domain of enterprise adoption and transformation. Enterprises are beginning to understand the consequences of the evolving artificial intelligence-driven automation ecosystem far beyond narrow artificial intelligence, crossing economic, commerce, learning, development, governance, logistics and trade. The force and pace of AI-driven automation change expected in the coming years will present each enterprise challenges and opportunities for its: products, services, processes, and operations. From what it seems, the AI applications of tomorrow will be hybrid systems composed of several components and reliant on many different data sets, methodologies, composite and complex models.

Speaker Profile

A well-seasoned professional with 18+ years of rich experience and an analytical thought leader with proven track records of enterprise first behaviours and skills - Productivity, Quality and Integrity.

10+ Years of Leadership, managed a larger teams, worked as Profit centre head, managed various units, time and cost-conscious Gut Leader with Project Management and Product Development skills. Very immense experience in the onsite-offsite business model. Have hands-on in Anaconda for Analytics – developed numerous AI products around Statistical Inference, Machine Learning, Deep Learning (CV + NLP) and Visualizations.

Passionate in the areas of Data Journalism (DJ), Edge Computing (IoT) and Bigdata Analytics. Hands-on in Pattern recognition, Anomalies Detection and behaviour analysis. Certified Six Sigma Black Belt; Proficient in Lean and Six Sigma; ESSA, DFSS, DOE, DMIAC Concepts and Principles; Specialist in Business Function Structuring; Eliminate waste, standardize, simplify and automate; Hands-on in Lean and six sigma tools such as Minitab16 and SigmaXL. Technical Expertise

Techno-functional excellence across Business Analytics and Business Intelligence Process Improvement projects. Have fair scripting skills in various languages VBA, SAS, SQL, R, Django, Flask, HTMl, CSS, JS, Groovy, C++, Julia, Hadoop Hive, Pig, Sqoop, Spark and Python. Hands-on in Anaconda Cluster, numpy, scipy, scikit-learn, Panda, cxOracle, Xlwings, pyODBC, hs2client, Matplotlib, Beautiful Soup, Selenium, Bokeh, Blaze, TensorFlow, pyDAAL and more Packages, word, powerpoint, excel and Access, Re-Engineered 600+ MI Processes. Technical support on Exploratory and Predictive Analytics, setting up Hadoop clusters, Apache Hadoop Ecosystems such as HDFS, Yarn, Map Reduce, HBASE, Hive QL and Pig Latin, Spark, MongoDB, Anaconda, and Revo-R. Hands-On in Implementing Microstrategy, Tableau, Qlikview, etc.

Creator of 4lens
Single-Handedly, Structured design and development of a cross-platform mobile and cloud android suite, named 4lens , otherwise called as “Smart Work Effort and Efficiency Tracker (Sweet)”. Sweet is a smart tracker to capture and report the productivity, efficiency and quality of information processing group. It helps to mitigate with the client on the day on day Business Analytics and Business Intelligence service delivery.

Other Academic Stuff
Advisor for HBR Publication, Member of HBR Advisory Council, Harvard Business Review, Member: ISACA; ASQ; International Council for Six Sigma; Harvard Square; Visit Faculty for SAS India and Alumni Mentor for AI Automation in Great Lakes.

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


Association partner

Digital Marketing Partner

Marketing Partner

Promotional & Media Partners

Our Past Sponsors

Media Partner


Our Speakers


IT Director


Anup Kumar Ray

Data Architect


Veerendra Thati

Big Data Analytics Architect


Nagaraju Chikoti

Practice Head, Manufacturing Analytics

Wipro technologies

Manoj Chiruvella

Principle QA Analyst


Ebenezer Bardhan

Associate Director - Data Analytics

Verizon India

Gurudatta Kamath

Practice Head of Data and Analytics

Tech Mahindra

Sitaram Tadepalli

Data scientist



IT Architect


Srinivasa Rao Jasti

Senior Technical Manager


Lakshminarshimhan Santhanam

Founder, CEO

Graspinor Analytics

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.