![\"Telecom](\"https:\/\/d17ocfn2f5o4rl.cloudfront.net\/wp-content\/uploads\/2022\/01\/body-im-telecom-4.jpg\")
<\/p>\nTaking data and analytics to the cloud is a winning strategy. Many people, particularly data scientists, mistake data for wisdom. They are distinguished by their maturity. Data tells you that the red thing is a tomato. Knowledge tells you that it\u2019s a fruit. But only wisdom tells you not to put it into a fruit salad. So data is raw, unrefined source material for knowledge. It needs the treatments of Comparison and Experience in order to be turned into wisdom.<\/p>\n
By nature, data is malleable, which is why it can be found in data lakes and, with the application of energy, it enables a telecom data warehouse migration to the public cloud. Should data, like the tomato, be put into the Fruit Salad that we call The Public Cloud?<\/p>\n
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What is data? Data is raw intelligence stripped of any context. Data types are as varied as the fruit family and they all contain fertile seeds that can germinate ideas.<\/p>\n
While fruits have three layers, the corporate data lake tends to have four layers, as the chart above illustrates and two categories of data pervading them. The data elements are the Relational Data, which tends to be deep and complex, and fast moving Streaming Data, which can easily wash over you.<\/p>\n
Both will be, by turns, subject to the stages of Ingestion, Distillation and Processing before finally (hopefully), emerging into Insights. It is worth outlining the differences between the two types of data.
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<\/div>\n\t\t\tRelational data comprises types like database tables and spreadsheets, which would typically be used in business departments and applications. Streaming data comes at you fast from sensor output, application logs and mobile interactions. This is the domain of the technical departments.<\/p>\n
![\"Telecom](\"https:\/\/d17ocfn2f5o4rl.cloudfront.net\/wp-content\/uploads\/2022\/01\/body-im-telecom-1.jpg\")
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Source: Nokia<\/a><\/em><\/p>\n A data lake is a bit like an industrial scale version of the \u2018data dump\u2019 that\u2019s performed when a business associate throws random abstracts at you and expects you to make sense of them. In both cases they operate on a \u2018store now, analyse later\u2019 basis.<\/p>\n The next phase of \u2018on premise\u2019 or \u2018in warehouse\u2019 data analysis was traditionally known as ETL (extract, transform, load) in which data was pulled and prepared for analysis.<\/p>\n However, the machinations of a modern communications service provider<\/a> run on sub-millisecond response times. Let’s examine how some systems integrators are migrating a telco to a public cloud.<\/p>\n There is a mismatch in form involved in a telecom data warehouse migration to public cloud<\/a>.<\/p>\n If, say, Spain\u2019s flagship mobile operator Telefonica wants to offer subscribers an upgrade on their data package the second they exceed their limit, as they celebrate a goal by Real Madrid, they need to do it instantly, before the excitement dies down.<\/p>\n So, the analytics tools for the telco cloud are quite different.<\/p>\n Moving the old Data Architecture of warehousing to the cloud may well fall short of your business requirements. The phrase telecom data warehouse migration to public cloud evokes images of castles in the air!<\/p>\n There are four qualities you must retain once your data has left the lake, the warehouse or the silo and heads into the cloud. You want to embrace an open architecture without being trapped in a database lock-in. Telecom cloud solutions<\/p>\n If you want as many brains – human and robotic – applying their analysis to a situation then by necessity you must grant ubiquitous access to the intelligence (aa the data) available. You will want to constantly refine it, so that it is constantly operational and maintains accurate historical integrity.<\/p>\n So, there are huge risks involved in moving data to the cloud. There seem to be three types of risk. The data types, the analytics and most ominously of all, the choice of cloud technology in the telecoms industry<\/a>.<\/p>\n Any object store such as Amazon S3 will be a good fit for the cloud. Amazon Web Services (AWS) also brings constant gratification. However, once it has wrapped itself all over your business processes and your data, it might be very difficult to extract the business if another service provider offers better options.<\/p>\n Less cost, more revenue, unlimited growth – this all sounds very easy. Obviously, the decisions about cloud migrations for any telco are anxiety-inducing strategic choices. Witness the industry machinations as telcos look for partners to help them with all the difficult decisions involved.<\/p>\n![\"Telecom](\"https:\/\/d17ocfn2f5o4rl.cloudfront.net\/wp-content\/uploads\/2022\/01\/body-im-telecom-2.jpg\")
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\n\n \n \n <\/div>\n <\/div>\n <\/div>\n Learn more<\/span>\n\t\t <\/a><\/div><\/p>\nHow telcos are moving analytics to the public cloud<\/h2>\n
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