EXPERT SPEAK on integrated layers of connected data and provides seamless , end-to-end integration of all data in multi-cloud environments .
At the same time , the Internet of Things ( IoT ) paradigm continues to advance , and data analytics will continue to extend to the edge of networks . Although it is true that companies use many more sensors than before , it is also true that people do not know how to take advantage of them . Therefore , this year , advanced analytics for IoT is expected to take this concept beyond simply visualizing sensor data to generate patterns . This process will integrate analysis , AI and decision intelligence into edge applications so that it is possible to analyze data almost in real-time .
In summary , the trend is for companies to develop a scalable and secure data infrastructure to continue harnessing the power of data . Along these lines , they will continue to move their analytics and data solutions to the cloud , incorporate systems to process real-time data , and use DaaS services to work with data without the need to build their own systems . Simultaneously , data governance will become increasingly important to protect customer privacy and comply with regulations .
Given that data analytics is becoming increasingly important in business as it enables informed decision-making , improves efficiency , identifies opportunities , provides a competitive advantage , and enhances the customer experience , there is no reason not to harness its potential right now . have to collect , clean , process and analyze it to transform huge volumes ( big data ) into information and from there into knowledge .
McKinsey anticipates that by 2025 , most employees will use data to optimize almost every aspect of their work . And it estimates that by that time vast networks of connected devices will collect and transmit them often in real-time .
Additionally , more sophisticated advanced analytics will be reasonably available to all organizations as the cost of cloud computing continues to decrease and more powerful data tools are online .
" Transforming into a data-driven organization enables : better understanding customers and responding to changes in their demands , personalizing commercial offerings , making overall management more efficient , having predictive
The use of Data-as-a- Service ( DaaS ) will gain popularity , which allows for data collection , management and storage by third parties through cloud services . capabilities , accelerating innovation and making better decisions . Under this context , today the cloud environment provides both solutions for storing large amounts of data , as well as the tools needed to work on its entire life cycle ," said Eugenia Lasta , VP Professional Services at BGH Tech Partner . Cloud platforms tend to accelerate the Digital Transformation of companies and help them become data-driven organizations . However , research by New Vantage Partners found that achieving data-driven leadership remains a difficult aspiration for most companies . Only 40 % reported managing data as a business asset and just 27 % said they had created a data-driven organization .
Advantages and challenges
While becoming data-driven provides companies with advantages such as acquiring and retaining customers , insights to optimize customer experiences , greater operational efficiency , and better economic results , doing so in the cloud environment is not so simple . It is essential to create a cloud data strategy that facilitates the task of preparing , analyzing and presenting data . And for this , a modern , flexible and scalable data architecture in the cloud is needed .
A report by Statista indicates that by 2022 , over 60 % of all corporate data will be stored in the cloud . This share reached 30 % in 2015 and has been growing as companies increasingly move their resources to cloud environments in the hope of improving security , reliability and business agility . •
Data as a business asset
Becoming a data-driven company has significant advantages such as acquiring customer expertise and increased operational efficiency . However , only 40 % of organizations manage data as a business ‘ asset ’.
Currently , in the business environment , it is common to hear frequently that ‘ data is the new oil ’. However , initially , data itself is raw material , to extract value from it , you
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