Why big data projects go wrong
Over the last decade the number of data sources and volume of data that businesses need to analyse has exploded. Businesses need to try and tackle this big data beast to stay competitive. Many have already tried to do this using a variety of approaches; in-house, off the shelf solutions, open source, all with different pros and cons. There are some key points that any business should take note of so their solution is scalable, secure and future proof.
Hear from Manjit Johal, CTO and Co-Founder at AVORA about the best ways to tackle your big data problem and how to avoid common mistakes.
Watch this webinar to learn:
- If a new big data project is what your business really needs.
- Whether you should build in-house or buy off the shelf.
- Where big data projects fail and what the commercial cost is when they go wrong.
- How we cracked the big data and analytics problem and what we learnt along the way.
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CTO and Co-Founder, AVORA
Manjit has been building software professionally for over 17 years, amassing experience in many different facets of software development across retail, defence, advertising, telecoms, logistics, eCommerce and finance. Manjit is the Co-Founder and CTO of AVORA, where he leads the engineering team with the goal of creating the next generation analytics platform that fuses together AI and Analytics to provide new ways for users to go from data to insight faster than ever.
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