I am currently researching a feature on real time analytics for Computer Weekly. This will form the introduction to an eBook, to appear in a few weeks’ time.
The piece will cover current trends in real time analytics. What is driving their use, which technologies are involved, how are they deployed, and above all, what are the business benefits?
The piece will establish what real time means, in terms of analytics, and how organisations structure their data collection, analysis and management processes, around the idea of a constant stream of data. And it will also examine the barriers that need to be overcome, to make all this work.
I am keen to hear from potential contributors — analysts, integrators and consultants, and potentially vendors (at the chief data scientist/CIO/CTO level – no sales people please) and from organisations using real time data.
If you have a suggested interviewee, please drop me an email with a few bullet points setting out their points of view, and availability for interviews from June 1st.
For Computer Weekly my next feature will look at the specific demands placed on storage architecture by artificial intelligence, machine learning, and analytics.
The piece will ask:
What different approaches to providing storage are there for these technologies?
What limits, performance considerations and bottlenecks exist with the different approaches?
What ways of providing storage for analytics are we likely to see in future?
The article will cover both on-premises and cloud-based storage, where relevant. I’m keen to include some real-world use cases if possible.
I am open to comment from industry professionals, consultants, analysts and CIOs working with AI. ML and analytics.
Deadline for leads: 1700hrs BST, Tuesday 23 June. As ever, please email in the first instance.
For Computer Weekly, I’m looking at the compliance issues around gathering, storing and processing unstructured data.
This article will examine the likely compliance risks in unstructured data, and suggest potential solutions. It will ask:
- What is unstructured data? How does it compare to structured and semi-structured data types?
- Why is compliance an issue at all?
- Why is achieving compliance of unstructured data potentially problematic?
- What are the key steps to achieving unstructured data compliance?
As businesses gather ever greater volumes of unstructured data, and develop new ways to process and analyse the information, compliance becomes increasingly important. This is especially the case when organisations start to combine data sets, and use advanced analytics to search for insights in the information. Does the original consent to hold and process the data carry over to this type of application? And what happens when unstructured data is mixed with other data sets?
For the piece I am keen to have comments from data scientists, compliance experts, academics, lawyers and end user IT organisations. As the deadline is quite short, please send pitches, initial comments and leads to me by 1200 London time, June 13th by email please.