A Bloomberg survey reveals that 38 percent of organizations say legacy systems do not meet their requirements and that budgetary constraints are a major problem. What's your take on this?
People are very cost-sensitive, and that's a big driver. They know they need to upgrade their technology, and that's a challenge as technology comes at a high cost initially.
There are two things people need to do - one is to ensure that at the end stage, they're actually lowering their overall operating costs, and that's not just the money they spend on the vendor, but the money that's actually spent internally. And then based on that, one has to design strategies that manage any overlapping costs. But as long as they're focused on lowering overall costs, in the end, they normally end up in the right place.
The second thing they need to manage is the risk of operating. They need to ask themselves if they're partnering with a high-quality vendor that actually helps them lower operating risks.
But ultimately, firms have to make bold decisions. If you continue running many multiple duplicated systems, you'll never really get big savings. This can also help organizations overcome the challenge posed by legacy systems.
Numerous studies have shown the added cost burden posed by dark data. What's Bloomberg's solution to minimize the costs incurred by hoarding data?|
Organizations do hoard a lot of dark data, some of which they do not even understand. Some of this data is valuable, but some can expose the organization to risks.
Bloomberg has invested in a very innovative solution called Bloomberg Vault which allows our clients to index all of their internal data and then be able to zero in on where their dark data sits. It gives them metadata around it and allows them to identify duplicated data.
Bloomberg Vault is a secure, hosted compliance solution that enables governance of communication data-based information, file analytics and trade reconstruction across the enterprise. It allows clients to run a very powerful compliance rules engines for their emails, chats, and social media platforms.
We at Bloomberg, strongly believe that dark data management is the next frontier of information governance.
A lot of organizations nowadays are deploying artificial intelligence and machine learning. What are the data management challenges organizations are faced with in these cases?
If I'm building a deep-learning system, I need to have the tools that I can apply to the data. But just because I have the tools, it doesn't mean I'm going to get anything valuable out of it. The machine needs to be able to ingest lots of data and make sense out of it.
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