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    Big Data Toronto 2018: Post-Event Highlights

    March 30th, 2022

    Team Astera participated in Big Data Toronto 2018 as an exhibitor and had a truly great experience networking with data scientists, practitioners, and thought leaders from across North America and beyond. We took the opportunity to introduce our end-to-end, agile data warehouse solution, DWAccelerator, and received a great response from the attendees.

    Event Overview

    Going strong in its third year, Big Data Toronto is among the most acclaimed big data and analytics conferences & expos in Canada. Over 4,000 innovators, 60+ exhibiting brands, and 100+ speakers gathered under one roof to embark on an educational journey and exchange technical insights, while providing an outlook on future trends of technology and best practices related to AI and data science.

    The conference, held in Metro Toronto Convention Centre, was a two-day event, and covered key topics, including digital transformation, data governance, data management, predictive analytics, advanced machine learning, cyber security and privacy, and more.

    Highlights of the Event

    Big Data Toronto 2018 has been a thought-provoking and insightful journey for our team. Here is what we learned from the conference:

    Agile Data Warehousing Practices

    Data warehousing, as a field, stays highly relevant for businesses in the big data era, albeit the expectations have changed significantly over time. Agility in design and development of warehouses has become a key requirement. Businesses are diligently seeking solutions that can accelerate core data warehousing functions, such as data integration, analysis, and cleansing for business intelligence, among others.

    Intelligent Data Extraction

    Businesses are increasingly taking interest in agile data warehousing solutions that offer effective data extraction from complex structured and unstructured sources, as well as traditional sources. They need accurate, intelligible results quickly to acquire analytical reports through business intelligence tools, allowing them to conform to the changing market dynamics, as well as for making sound decisions for future endeavors.

    Astera DW Builder – The Solution to Major Data Warehousing Problems

    Massive setup costs, time-consuming processes, and lack of agility and flexibility are some of the key obstacles met during BI project implementation. DWAccelerator can very well be the answer to all these issues. DWA is an all-round solution that instills agility and automation in data warehouse designing and development without having the user write a single line of code.

    Our COO, Jay Mishra, conducted a session on “Accelerating your Data Warehouse Project” and shed light on problems and ways for businesses to speed up setting up a data warehouse. He presented DWAccelerator and showed that while a data warehouse, using traditional techniques, takes anywhere from a few weeks to several months to build, it can be done in under an hour with our automated solution. Some of the highlighting features of DWAccelerator, such as data models based mapping, automatic field matching, flow generation, and the concept of virtual data models, were well received.

    We Met Prospective Partners and Clients

    The innovative features and powerful data warehousing capabilities of DWAccelerator gathered much attention from the attendees. We talked to many data professionals and showcased how our product can automate the entire data warehousing process and cut down the costs and time required. This generated a lot of interest in our product, inspiring several new partners and prospective clients to join hands with Astera.

    Overall, Big Data Toronto 2018 offered a plethora of insights and concepts that are likely to pave way for future technologies and trends. In addition, the Canada’s #1 big data and AI conference proved to be a great opportunity for us to meet new clients and partners and provide exposure to the latest addition to our product line, DWAccelerator.

    Authors:

    • Irfan Ahmed
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