Tired of lengthy data integration processes in your day to day database activities?
With the IBM InfoSphere DataStage, data integration can be streamlined across multiple applications by utilising its multi-cloud platform.
Using AI and Big Data has become the norm to get work done in day to day life. In the meantime, it's essential to keep in mind that AI and Big Data has given life to a range of new cybersecurity challenges as well. If you are planning to reap the benefits that come along with AI and Big Data, you need to have a basic understanding of these challenges. Having this understanding will ensure your businesses security and protection in the long run.
Every enterprise has a mix of software solutions to address the various challenges they experience in their data management lifecycle. Data governance, data protection, and security, native storage and hybrid cloud management, data cataloging , data accessibility, reporting – are just some of the data challenges data stewards deal with daily.
When you are working as a data analyst for a company, you will often find difficulties in getting your hands on data. When proper data is not available, it can also be challenging to analyse it on time. This is where you need to think about using a data catalog.
By combining technical and business processes to merge data into valuable information, data integration delivers trusted data from several sources to help marketers build a clearer picture of their target market.
Every minute, 1.7 megabytes of data is created for every person on the planet. All 7.3 billion of us!
In its latest report Gartner suggests that 80% of this growing data in unstructured and business data. So even with data storage becoming cheaper are we up to the challenge of managing this explosive growth of data?
Get your data ready for AI with IBM Could Private for Data
At the Dot Group, we can’t stress enough about the importance of a robust information architecture in order to monetise your data. Artificial Intelligence enabled analytics can provide insights into customer behavior, business operations and offer a humongous opportunity for business to provide personalized/exceptional customer service, reduce the cost of operations and create offerings to beat competition. However, let’s not forget that AI and analytics are only as good the quality of your data.
Cognitive capabilities and hybrid cloud technology are playing an increasing part in how industries utilise their data. Discover how data management platforms are transforming customer care.
As customer expectations rise, so too is the awareness that companies need to meet rising expectations if they want to thrive in today’s marketplace. But while many businesses will admit to prioritising customer service, it can be difficult to make effective decisions in this area without the means of gathering and analysing the data needed to back them up.
The question that gets to the heart of this is: “Are you confident you know what you’ve got lurking around your networks, and where?” However, this risks oversimplifying what is an incredibly versatile business asset. Let’s examine where we are today, and why Discovery is a tool you should be relying on. So what are typical use cases for intelligent discovery software?
How much confidence do you have that you know what’s lurking in the dark corners of your server room, or in that datacenter you only just realised you’re still paying for? What about sensitive data uploaded to a semi-public cloud that really the HR department should have stopped using several years ago? Efficiency savings, regulatory compliance and a tight security posture are all top priorities for any IT leader. But visibility underpins them all.