Experts at Quantzig Analyze the Correlations and Functionalities of Data Lakes, Analytics, and Machine Learning in Their Recent Article

LONDON--()--Given the hype around data management, it is close to impossible to dismiss the use of data lakes as a small step forward in an already accustomed technology realm. Notably, it’s not the implementation of new technology that matters now, as much as what it enables organizations to do using data. By making data easily accessible for everyone within an organization, data lakes are slowly turning out to be the fundamental driving forces behind innovation and disruption across industries.

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Moreover, as data grows and diversifies, many organizations are finding that traditional methods of data management are now becoming outdated. Quantzig, in its recent article, aims to understand the performance implications, common characteristics, and critical capabilities that need to be considered while building and maintaining data lakes as a common source for all business-critical data.

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“Now’s the time for companies to invest in data lakes and analytics to avoid being left behind in the race to success,” says an analytics expert at Quantzig.

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As organizations are now actively building data lakes and investing in analytics platforms, they need to reconsider several critical capabilities, including:

Real-time Data Movement: Data lakes enable businesses to import and store data in different formats and from various sources in real-time. Adopting such a method for data storage and analysis enables businesses to scale to data of any size while saving time of defining data structures, schema, and transformations.

Data Storage: By storing data in data lakes, businesses gain the ability to crawl, process, and index the data to better understand the data being stored. Apart from real-time transactional data, it enables businesses to store relational data and data from line of business applications, and non-relational data like mobile apps, IoT devices, and social media.

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Analytics Platforms: Data lakes empower data scientists, data developers, and business analysts to access data with their choice of analytic tools and frameworks. This also enables businesses to run analytics without the need to move your data to a separate analytics system.

Machine Learning: Data lakes enable organizations to generate reports and insights that aid decision making using historical data modeling and machine learning techniques to forecast outcomes and prescribe actions to achieve the desired result.

In the analytical process of decoding unstructured data to extract actionable insight, a well-defined data lake strategy is proven to produce relevant insights promptly. Also, when the movement of data is frictionless and trustworthy, companies can discover and act upon immediate opportunities for driving growth and efficiency.

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About Quantzig

Quantzig is a global analytics and advisory firm with offices in the US, UK, Canada, China, and India. For more than 15 years, we have assisted our clients across the globe with end-to-end data modeling capabilities to leverage analytics for prudent decision making. Today, our firm consists of 120+ clients, including 55 Fortune 500 companies. For more information on our engagement policies and pricing plans, visit: https://www.quantzig.com/request-for-proposal

Contacts

Quantzig
Eva Sharma
Marketing Manager
US: +1 630 538 7144
UK: +44 208 629 1455
https://www.quantzig.com/contact-us

Release Summary

Quantzig announces the completion of its recent article that lists the critical requirements for building and maintaining data lakes.

Contacts

Quantzig
Eva Sharma
Marketing Manager
US: +1 630 538 7144
UK: +44 208 629 1455
https://www.quantzig.com/contact-us