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The data-centric enterprise: Not yet a done deal

In today’s digital era, a new type of asset is emerging: data. What oil was to the 20th century is what is data has become in the 21st century — an engine that propels change, economic growth, competitiveness, and innovation. Enterprises are gathering, storing, refining, and analyzing vast amounts of data.

In the digital age, data will be the essential input factor and determinant of a company’s future success. However, many companies are operating within a fragmented IT landscape and struggle with increasing complexity. This often thwarts their efforts to make informed business decisions, take advantage of the data economy and monetize their efforts. After surveying more than 500 IT executives from enterprises across a variety of countries including Australia, Brazil, Canada, China, France, Germany, Japan, the United Kingdom and the United States, SAP revealed a wide variety of issues associated with enterprise data in their Data 2020: State of Big DataBig Data describes data collections so big that humans are not capable of sifting through all of it in a timely manner. However, with the help of algorithms it is usually possible to find patterns within the data so far hidden to human analyzers.  study. Here are five key findings:

1. Data is siloed, inaccessible and unhealthy

Half of respondents think that data is siloed and inaccessible to a wide variety of business stakeholders, which hinders enterprises from fully exploiting their data lakes. Due to rising data complexity, enterprises are not as agile and data-driven as they need to be. While 83 percent would benefit from a data integration solution, 79 percent think their company’s data needs more than just a checkup to make it healthy.

2. Data is still primarily stored on-site, but is often enriched with external sources

Despite the widespread enthusiasm about , 37 percent of data is still held on premises. Only 26 percent is stored in private or public clouds. However, enriching existing data with data sourced from outside the enterprise has become common practice, with 68 percent of all respondents taking advantage of it. This, for example, includes Enterprise Applications such as CRM or ERP (cited by 72 percent) and third-party data sources (cited by 54 percent).

3. Data strategies still focus on quantity rather than quality

Roughly three quarters (74 percent) of respondents think their data landscape is so complex that it limits their corporate agility. Another 86 percent say they are not getting the most out of their data and that there is much more they could do with it. While three out of four enterprises (74 percent) do regular cleanups, a mere 23 percent of all respondents consider their data to be of high quality, which suggests that many companies are overwhelmed with ever-increasing volumes and struggling to turn big data into “good data”.

4. Analytics are driving data-minded enterprises

Companies clearly see the need to upgrade their capabilities going forward. Analytics (cited by 96 percent) tops the list of technologies most important to harness the power of big data and derive strategic insights. This is followed by the Internet of Things (cited by 85 percent), Machine LearningSimilar to humans, machines learn through experience, e.g. seeing data. This process of presenting data to an algorithm and seeing improvement in the performance/accuracy is called machine learning.  and (each cited by 81 percent).

5. Data scientists are in short supply

While 79 percent of respondents say that data scientists are pivotal to ensure a company’s success, just half (53 percent) currently have data scientists on their payroll. As demand outweighs supply, 78 percent of respondents worry that a talent shortage could impede their efforts to become a data-centric organization. […]

  1. SwissCognitive

    The data-centric enterprise: Not …
    #Artificial_Intelligence #Cloud_Computing #Deep_Learning #Machine_Learning
    https://t.co/JXvzFKQprT

  2. Peter Kalberer

    The data-centric enterprise: Not yet a done deal – https://t.co/dOqSadm3n5

  3. Peter Kalberer

    The data-centric enterprise: Not yet a done deal https://t.co/2ft52Q5mlg

  4. Peter Kalberer

    The data-centric enterprise: Not yet a done deal https://t.co/DKUIuyiL2z via @SwissCognitive

  5. James Douglass

    RT @SwissCognitive: The data-centric enterprise: Not …
    #Artificial_Intelligence #Cloud_Computing #Deep_Learning #Machine_Learning
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  6. Dalith Steiger

    The data-centric enterprise: Not …
    #Artificial_Intelligence #Cloud_Computing #Deep_Learning #Machine_Learning
    https://t.co/ET87cXsda1

  7. Andy Fitze

    The data-centric enterprise: Not …
    #Artificial_Intelligence #Cloud_Computing #Deep_Learning #Machine_Learning
    https://t.co/nAgBPf7mxH

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