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too good value proposition for businesses to let it go : take massive
amounts of data they accumulate inside and outside their organization,
and extract valuable information among the countless worthless data .
But these chips can be tiny and very hard to find.
Companies are progressing in the organization and review of internal data, such as interactions in call centers, business transactions and product levels. However, they are not prepared to external information. But in the end, what is the essence of large amounts of data, it is the external information on the web, including social media. However, most companies are wary of the validity or accuracy of this data.
These are the conclusions of a report recently published by IBM and the Saïd Business School, Oxford University, based on a global survey of 1,144 business professionals and IT. Three-quarters (76%) of respondents currently conducting Big Data development initiatives, mainly in the early stages.
Most of Big Data initiatives currently deployed by companies aim to improve the customer experience. Yet, despite this focus, less than half of the companies involved in these initiatives collect and analyze data from external sources, such as social media. This is explained by the fact that business leaders fear the uncertainty inherent in certain types of data, such as weather, the economy or the feeling and sincerity of the people who speak out on social networks. Respondents in the study have questioned their ability to trust comments, reviews, micro-messages or other forms of freely shared online opinions.
As the report states: "The feelings and sincerity among individuals, the GPS signals that bounce off the skyscrapers of Manhattan, weather conditions, economic factors, the future ... Faced with these kinds of data, the data cleansing is ineffective. Yet despite the uncertainty, these data do not contain less valuable information. The need to recognize and accept this uncertainty is a fundamental characteristic of Big Data. »
The second major problem is a growing shortage of skills when it comes to find individuals capable of managing and retrieving the data, the study reveals. Only 25% of respondents in the study said they have the capacity to analyze highly unstructured data, which is a major obstacle to get the most value from large amounts of data.
Indeed, the Big Data requires to analyze semi-structured and unstructured data, including various types of data that can be entirely new for many companies. Obtaining the advanced capabilities required to analyze unstructured data (data that do not fit in traditional databases, such as text, sensor data, geospatial data, audio, images and video), and broadcast data continuously remains a major challenge for most companies.
A competitive advantage that almost two thirds of respondents
The respondents in the study cite different advantages and business opportunities arising from their Big Data projects. Nearly two-thirds (63%) of respondents said that the use of information, including Big Data and analytical processing "creates a competitive advantage" for their business. This represents an increase of 70% compared to 37% who saw it as a competitive advantage in an IBM study in 2010.
More than half of respondents in the study cited internal data (this is usually structured data) as the main source of large amounts of data in their business. In more than half of the active efforts of Big Data, respondents have entrusted use advanced capabilities to analyze the text in its natural state, such as transcripts of conversations in call centers.
These analytical capabilities include the ability to interpret and understand the nuances of language, such as felt, slang and intentions. This data can help companies such as a bank or a telecom service provider to understand the state of mind of a client and obtain valuable information that can be immediately exploited to guide customer management strategies.
Besides the results focused on customers, only half (49%) of respondents identified as a high priority, the first applications of Big Data are addressing other functional objectives. Almost a fifth (18%) of respondents cited optimizing operations as a primary goal. Other Big Data applications are focused on the financial and risk management (15%), empowering new business models (14%) and employee collaboration (4%).
Companies are progressing in the organization and review of internal data, such as interactions in call centers, business transactions and product levels. However, they are not prepared to external information. But in the end, what is the essence of large amounts of data, it is the external information on the web, including social media. However, most companies are wary of the validity or accuracy of this data.
These are the conclusions of a report recently published by IBM and the Saïd Business School, Oxford University, based on a global survey of 1,144 business professionals and IT. Three-quarters (76%) of respondents currently conducting Big Data development initiatives, mainly in the early stages.
Most of Big Data initiatives currently deployed by companies aim to improve the customer experience. Yet, despite this focus, less than half of the companies involved in these initiatives collect and analyze data from external sources, such as social media. This is explained by the fact that business leaders fear the uncertainty inherent in certain types of data, such as weather, the economy or the feeling and sincerity of the people who speak out on social networks. Respondents in the study have questioned their ability to trust comments, reviews, micro-messages or other forms of freely shared online opinions.
As the report states: "The feelings and sincerity among individuals, the GPS signals that bounce off the skyscrapers of Manhattan, weather conditions, economic factors, the future ... Faced with these kinds of data, the data cleansing is ineffective. Yet despite the uncertainty, these data do not contain less valuable information. The need to recognize and accept this uncertainty is a fundamental characteristic of Big Data. »
The second major problem is a growing shortage of skills when it comes to find individuals capable of managing and retrieving the data, the study reveals. Only 25% of respondents in the study said they have the capacity to analyze highly unstructured data, which is a major obstacle to get the most value from large amounts of data.
Indeed, the Big Data requires to analyze semi-structured and unstructured data, including various types of data that can be entirely new for many companies. Obtaining the advanced capabilities required to analyze unstructured data (data that do not fit in traditional databases, such as text, sensor data, geospatial data, audio, images and video), and broadcast data continuously remains a major challenge for most companies.
A competitive advantage that almost two thirds of respondents
The respondents in the study cite different advantages and business opportunities arising from their Big Data projects. Nearly two-thirds (63%) of respondents said that the use of information, including Big Data and analytical processing "creates a competitive advantage" for their business. This represents an increase of 70% compared to 37% who saw it as a competitive advantage in an IBM study in 2010.
More than half of respondents in the study cited internal data (this is usually structured data) as the main source of large amounts of data in their business. In more than half of the active efforts of Big Data, respondents have entrusted use advanced capabilities to analyze the text in its natural state, such as transcripts of conversations in call centers.
These analytical capabilities include the ability to interpret and understand the nuances of language, such as felt, slang and intentions. This data can help companies such as a bank or a telecom service provider to understand the state of mind of a client and obtain valuable information that can be immediately exploited to guide customer management strategies.
Besides the results focused on customers, only half (49%) of respondents identified as a high priority, the first applications of Big Data are addressing other functional objectives. Almost a fifth (18%) of respondents cited optimizing operations as a primary goal. Other Big Data applications are focused on the financial and risk management (15%), empowering new business models (14%) and employee collaboration (4%).
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