{"id":41921,"date":"2021-03-18T16:41:18","date_gmt":"2021-03-18T16:41:18","guid":{"rendered":"http:\/\/icloud.pe\/blog\/?guid=45d6b1951af457418a7d56272f475eab"},"modified":"2021-03-18T16:41:18","modified_gmt":"2021-03-18T16:41:18","slug":"cloud-can-help-you-understand-data-but-only-if-you-plan-first","status":"publish","type":"post","link":"https:\/\/icloud.pe\/blog\/cloud-can-help-you-understand-data-but-only-if-you-plan-first\/","title":{"rendered":"Cloud can help you understand data \u2013 but only if you plan first"},"content":{"rendered":"


\n Sandra Vogel<\/a><\/span>
\n <\/span><\/p>\n

\n
\n
18 Mar, 2021<\/span><\/div>\n<\/p><\/div>\n<\/div>\n

\n<\/a><\/p>\n

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Organisations might be drawn to cloud by the lure of gaining new information and insights from the data they hold. Perhaps they will learn how to retain customers more successfully, or get a better understanding of profit centres \u2013 or cost centres. The twin powers of <\/span>artificial intelligence and machine learning (AI and ML)<\/span><\/a>, deployed in the cloud can work wonders. But they need their \u2018food\u2019, the raw data they work with, to be in tip top condition, and for many organisations preparing that food requires time, effort, and attention to detail.\u00a0<\/span><\/p>\n

Data strategies and clear priorities\u00a0<\/span><\/h2>\n

There is no doubt that <\/span>AI<\/span><\/a> and <\/span>ML<\/span><\/a> can provide information that organisations can\u2019t come by in any other way. <\/span>Data-crunching<\/span><\/a> can, if done well, help organisations boost productivity and profits. But optimal success doesn\u2019t come overnight. As Yann Lepant, MD for Accenture Technology in the UK tells <\/span>Cloud Pro<\/span>: \u201cIt\u2019s easy to get tempted by the extensive set of cloud based new data and <\/span>AI technologies<\/span><\/a> as it\u2019s an exciting new playground to venture on. However, it\u2019s also a place where it\u2019s easy to consume wastefully and get lost in delivery.\u201d<\/span><\/p>\n

A key factor in avoiding the pitfalls is to have clear priorities and a solid data strategy. Lepant tells <\/span>Cloud Pro<\/span> that having these will mean \u201ceach initiative is done with purpose and outcome, contributing to a journey of maturation through the cloud\u201d.<\/span><\/p>\n

Ingrid Verschuren, head of data strategy at Dow Jones, whose global news database Factiva grows by a million articles every day, from approximately 33,000 sources, tells <\/span>Cloud Pro<\/span>: \u201cIt doesn\u2019t matter how good the technology is if the data feeding it is poor quality. The first and most important step to get the most out of your data is to ensure you are using the right data \u2013 and that it is structured in a way that will answer the questions you want to ask.\u201d\u00a0\u00a0<\/span><\/p>\n

So what do clear priorities look like? Paul Clough,<\/span> <\/span>professor of search and analytics at the University of Sheffield tells <\/span>Cloud Pro<\/span>: \u201cIdentifying the use cases is critical and needs to be based on issues and problems identified in the business by business stakeholders, rather than by data scientists or the IT department.\u201d This approach keeps the priorities very practically focused, he says.\u00a0<\/span><\/p>\n

Cleaning and refining<\/span><\/h2>\n

Another pair of related tasks that may need to be undertaken before AI and ML can work their magic are cleaning up old data and refining what new data is collected.<\/span><\/p>\n

Part of the cleaning task will involve bringing data out of silos. This can be tricky, but worth the effort and organisations undertaking the task can take some comfort from the fact that they\u2019re not alone. Often, data silos are a result of historical practice and how things have grown organically over time, and it takes a concerted effort to undo in a relatively short time what\u2019s built up over a much longer period. But as Lepant points out, there are really no short-cuts. \u201cFrom getting a 360 degree view of the customer to end-to-end supply chain management, via fraud prevention and intelligent forecasting, the list of business outcomes enabled by the removal of data silos is endless,\u201d he says.<\/span><\/p>\n

Cleaning data is another task that can take time, but the effort is definitely worth it in the longer term. Verschuren provides some useful advice to help keep the cleaning task focussed, telling <\/span>Cloud Pro<\/span>: \u201cBefore you start cleaning your data, you need to determine how that data will be used and what insights you need to generate. Ask yourself, what does perfect look like? From there, you need to define the data fields that will be part of your data set, and the input for each of those fields.\u201d Effectively, work backwards from the outcomes you want to get, and determine what data you need to get them.\u00a0<\/span><\/p>\n

And finally, along come analytics and insights<\/span><\/h2>\n

With clean data, a clear data strategy in place, and perhaps some new data collection streams in place too, an organisation is finally in a position to start using AI and ML to gain those valuable insights it craves.<\/span><\/p>\n

But that\u2019s not quite the end of the story. To continue to gain insights over time, data should take its place, unsiloed, front and centre. Or, as Lepant tells <\/span>Cloud Pro<\/span> when sharing key advice, organisations should \u201cimplement a programme to update the ways of working, culture and data literacy to help the business become more data driven and self-served\u201d.<\/span><\/span> <\/p>\n<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"

Sandra Vogel<\/p>\n

18 Mar, 2021 <\/p>\n

Organisations might be drawn to cloud by the lure of gaining new information and insights from the data they hold. Perhaps they will learn how to retain customers more successfully, or get a bet…<\/p>\n","protected":false},"author":438,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-41921","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/41921","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/users\/438"}],"replies":[{"embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/comments?post=41921"}],"version-history":[{"count":2,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/41921\/revisions"}],"predecessor-version":[{"id":41929,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/posts\/41921\/revisions\/41929"}],"wp:attachment":[{"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/media?parent=41921"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/categories?post=41921"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/icloud.pe\/blog\/wp-json\/wp\/v2\/tags?post=41921"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}