How to build better data products

Neeraj Gehani, Product Director at dunnhumby, made a case for having a product mindset at the fourth edition of the Machine Learning Developers Summit (MLDS) during his session titled ‘Emergence of Data Products.’ He unpacked the reasons for data products becoming increasingly important, types of data products, the framework for building data products and the unique challenges in building data products.


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How to build better data products
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iOS App Dev


Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Gerhard  Brink

Gerhard Brink


Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.


As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).

This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

Java Questions

Java Questions


Top Data Science Products Build In India - 2020

Analytics India Magazine brings the list of leading analytics and data science products for the year 2020 that have positively impacted businesses across the globe, helping them make decisions. To source the best 10 products, we reached out to more than 25 companies. Ranging from serving financial sectors to manufacturing, retailsolar and other industries, these products have made a significant impact on driving business value for the companies.

_Please note that this is not a ranking and the list is in no particular order. _

Cora Finance Analytics By Genpact

Cora Finance Analytic by Genpact is a comprehensive and persona-based financial analytics suite that enables data-driven decision making for finance professionals across all business units and functions. It aims at driving faster business outcomes by augmenting the evidence-based decision making cycle through Robust Data Foundation Layer, Advanced Analytics, Data Science Application, Domain Expertise and Smart Processes. It is built on a domain-centric data platform and can do real-time and API-based integration, including semi-structured and unstructured data.

**Key Differentiation Factor: **It is a technology platform agnostic and can be easily embedded into clients’ business workflows in any production environment — On-Prem, Cloud or Hybrid.

**Client, Sectors and Geographies Served: **It is being used by over 25 clients across sectors such as hi-tech, manufacturing and services, consumer packaged goods and retail. It serves across geographies such as the US, Europe, Asia, Australia.

About the Company: A global professional services firm, Genpact drives digital-led innovation and digitally-enabled intelligent operations for clients guided by deep experience in data and analytics. Headquartered in New York, it operates in more than 25 countries, accelerating the digital transformation to create bold, lasting results.

Prediction, Anomaly Detection By Quadrical AI

Working with the Renewable Industry (right now only Solar), Prediction by Quadrical AI helps companies maximise their returns on solar fields by assisting them in predicting with much higher precision exactly how much energy they will produce. It also points out faults, fissures and failures so they can be fixed. Using AI, they can track degradations to turn unplanned maintenance to planned maintenance. The platform further keeps learning and improving with time, reducing maintenance costs, and allowing for greater Return-on-Assets for the Solar companies.

Key Differentiation Factor: With Digital Twin technology, it aims to build an identical digital twin of the plant to make it an energy-efficient world.

#featured #analytics products india #data science products 2020 #data science products build in india 2020 #data science products india

Cyrus  Kreiger

Cyrus Kreiger


How Has COVID-19 Impacted Data Science?

The COVID-19 pandemic disrupted supply chains and brought economies around the world to a standstill. In turn, businesses need access to accurate, timely data more than ever before. As a result, the demand for data analytics is skyrocketing as businesses try to navigate an uncertain future. However, the sudden surge in demand comes with its own set of challenges.

Here is how the COVID-19 pandemic is affecting the data industry and how enterprises can prepare for the data challenges to come in 2021 and beyond.

#big data #data #data analysis #data security #data integration #etl #data warehouse #data breach #elt

Macey  Kling

Macey Kling


Applications Of Data Science On 3D Imagery Data

CVDC 2020, the Computer Vision conference of the year, is scheduled for 13th and 14th of August to bring together the leading experts on Computer Vision from around the world. Organised by the Association of Data Scientists (ADaSCi), the premier global professional body of data science and machine learning professionals, it is a first-of-its-kind virtual conference on Computer Vision.

The second day of the conference started with quite an informative talk on the current pandemic situation. Speaking of talks, the second session “Application of Data Science Algorithms on 3D Imagery Data” was presented by Ramana M, who is the Principal Data Scientist in Analytics at Cyient Ltd.

Ramana talked about one of the most important assets of organisations, data and how the digital world is moving from using 2D data to 3D data for highly accurate information along with realistic user experiences.

The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment, 3D data for object detection and two general case studies, which are-

  • Industrial metrology for quality assurance.
  • 3d object detection and its volumetric analysis.

This talk discussed the recent advances in 3D data processing, feature extraction methods, object type detection, object segmentation, and object measurements in different body cross-sections. It also covered the 3D imagery concepts, the various algorithms for faster data processing on the GPU environment, and the application of deep learning techniques for object detection and segmentation.

#developers corner #3d data #3d data alignment #applications of data science on 3d imagery data #computer vision #cvdc 2020 #deep learning techniques for 3d data #mesh data #point cloud data #uav data