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Overcome security concerns when moving big data to the cloud
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Riding the elephant: how to manage big data
Among all the talk in recent years about what big data is, and what organisations could do with it, there has been a bit missing about how to manage big data programmes and projects, which is a prerequisite of gaining business value from the analytics done on the data.
Big data vendors – such as the Hadoop distributors – will say they see signs that big data science projects are giving way to large scale implementations. But how are user organisations managing those? How are they designing their IT organisations, and the rest, to manage and capitalise on big data?
The lead article in this e-guide is focused on the management of big data. You can also read about the progress of open source parallel processing framework Apache Spark as, in part, a replacement for the MapReduce framework that was so important to an earlier generation of the Hadoop family of technologies; Spark also goes beyond the Hadoop Distributed File System [HDFS] to encompass relational and non-relational databases.
You can also hear about how Hadoop is starting to appear in earnest in the UK public sector, and how another stripe of big data technology, NoSQL databases, is making its mark for specific use cases.
Finally, you can find out how Autodata, a UK-based vehicle data company is using open source technology, including, potentially, Hadoop, to leverage big data to predict vehicle failures.
These are also closely related to: "Overcome security concerns when moving big data to the cloud"
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CW Middle East - October-December 2020: Egypt's datacentre plans take a step forward
While it builds an IT services industry, Egypt is also investing in infrastructure and now plans to develop a datacentre industry. Read in this issue how, as part of this plan, Egypt’s parliament has passed a data protection law. Also read how the Europe, Middle East and Africa region has seen traditional IT outsourcing deals reduce in value by 21%, while the business process outsourcing market fell by 9%.
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New wave BI and analytics: turning modern data stores to account
New generation data stores, such as the Hadoop family and the NoSQL databases, are not everything. Relational databases are not going away. Nevertheless, post- or non-relational data stores and databases pose new demands on the “front end” of data management – Business Intelligence and data analytics.
This e-guide looks at how companies and other organisations are doing BI and analytics on the newer data stores.
Financial services companies are active in this area, and we see re-insurer Munich Re combining a Hadoop data lake, SAS analytics and SAP Hana to create new cyber and other insurance services. Over in Dublin, Allied Irish Bank is blending artisanal data analytics work with a more “industrial” approach, drawing on both a Teradata data warehouses with an Hadoop cluster from IBM. And Nordics bank Danske Bank has been using the Hortonworks distribution of Hadoop as a resource for its data science programme to combat fraud, among other use cases.
On the vendor side, we find Looker’s CEO Frank Bien advancing the case that old-school BI is not adequate to the new generation of data stores while MicroStrategy CEO Michael Saylor counters that, in his view, “the world is not shifting from relational to big data, it is expanding in different dimensions simultaneously”.
Meanwhile, in Silicon Valley, we find a group of startup and early-stage data analytics and management companies aiming to make big data, including sensor data, more tractable for analysis.
