Post by account_disabled on Mar 5, 2024 1:15:25 GMT -5
In today's environment of data abundance and frequent information overload, the ability to discover single insights enables organizations to improve decision making. Big data analytics results in the ability to seize opportunities , minimize risks and control costs. It means extracting business value from data in real time. Because big data analytics is not just about managing more or more diverse data . Instead, it tries to raise new questions and formulate new hypotheses . It is exploring and discovering. It means making decisions based on data and eliminating subjectivities. As The Data Warehousing Institute explains in one of its 2012 reports, big data analytics is the application of advanced analysis techniques to large data sets. According to the October 2013 report prepared by TDWI , business reality shows that: - 57% of companies already interact with big data. - Among those surveyed, 61% choose big data analytics to manage big data. - The biggest problems related to big data are the lack of skills in 40% of cases and the complexity of integration in 30%.
Photo credits: "3d Concept Illustration Of Analytics Business Analysis" by David Castillo Dominici Big data analytics when? Many companies have been working with big data for a few years and, for much longer, businesses have been analyzing their data... but today the competition has reached its maximum level with big data analytics . Not everyone can claim to analyze all of their data. Those who are ahead know that they have achieved a competitive advantage that gives them a distance that is difficult for their competitors to close. In this case, not only size matters but speed also counts in favor. The challenges of big data analytics, and where a good solution differentiates itself from the Chile Mobile Number List rest, are: Predictive analysis . The processing of complex events. Business rules management . Your BI possibilities. Data integration . It must be taken into account that advanced analysis must consider operational data, online data from customers, data from sales and transactions, and data from equipment and production. All this without forgetting the essential ingredient, the key to the advantage: providing information about innovation in the service. Through knowledge of the business, in absolute terms, opportunities can be detected and taken advantage of. You need expertise and you need a strategy, but the tool is the first step to be able to think of a plan. Who is big data analytics for? Big data is a new generation of technologies and architectures, designed to extract economic value from large volumes of heterogeneous data, guaranteeing its capture, discovery and analysis in high-speed conditions. In view of this definition it is clear that there are no limits.
Nor are there any in terms of the size of the company that big data analytics is aimed at or its sector. There will be those who look for a global data scenario, where complete data sets are managed; and there will be those who need a more specific scenario, which is based on advanced analytics and data and metadata management tools to discover which data corresponds to a specific analytical model, when taking the total information into consideration does not provide extra value . Big data analytics is used by companies that want to deepen their self-knowledge, that want to get closer to their customers, exploit all the possibilities that their business allows and distance themselves from the competition. It is not just a matter of gigabytes or terabytes, but rather it is about the value that can be achieved and the creativity that will contribute to using it to grow and develop as an organization. Some big data analytics success stories are: The Climate Corporation . DollarGeneral . Netflix . The keys to follow your steps are: Do not leave aside the business perspective when working with data. Find the ideal way to take advantage of available resources. Aim for continuous improvement. Take into account the learning curve of advanced analytics. Set goals, review them, adjust them and keep working. Do you consider your data a resource or an asset? The era of "time is money" has come to an end. Today data is gold and big data analytics is the vehicle to turn the golden dream of the business future into reality. What is yours? Related posts: BI analysis of customer trends and behavior The future of the tourism sector depends on Big Data Top Five Big Data Applications.
Photo credits: "3d Concept Illustration Of Analytics Business Analysis" by David Castillo Dominici Big data analytics when? Many companies have been working with big data for a few years and, for much longer, businesses have been analyzing their data... but today the competition has reached its maximum level with big data analytics . Not everyone can claim to analyze all of their data. Those who are ahead know that they have achieved a competitive advantage that gives them a distance that is difficult for their competitors to close. In this case, not only size matters but speed also counts in favor. The challenges of big data analytics, and where a good solution differentiates itself from the Chile Mobile Number List rest, are: Predictive analysis . The processing of complex events. Business rules management . Your BI possibilities. Data integration . It must be taken into account that advanced analysis must consider operational data, online data from customers, data from sales and transactions, and data from equipment and production. All this without forgetting the essential ingredient, the key to the advantage: providing information about innovation in the service. Through knowledge of the business, in absolute terms, opportunities can be detected and taken advantage of. You need expertise and you need a strategy, but the tool is the first step to be able to think of a plan. Who is big data analytics for? Big data is a new generation of technologies and architectures, designed to extract economic value from large volumes of heterogeneous data, guaranteeing its capture, discovery and analysis in high-speed conditions. In view of this definition it is clear that there are no limits.
Nor are there any in terms of the size of the company that big data analytics is aimed at or its sector. There will be those who look for a global data scenario, where complete data sets are managed; and there will be those who need a more specific scenario, which is based on advanced analytics and data and metadata management tools to discover which data corresponds to a specific analytical model, when taking the total information into consideration does not provide extra value . Big data analytics is used by companies that want to deepen their self-knowledge, that want to get closer to their customers, exploit all the possibilities that their business allows and distance themselves from the competition. It is not just a matter of gigabytes or terabytes, but rather it is about the value that can be achieved and the creativity that will contribute to using it to grow and develop as an organization. Some big data analytics success stories are: The Climate Corporation . DollarGeneral . Netflix . The keys to follow your steps are: Do not leave aside the business perspective when working with data. Find the ideal way to take advantage of available resources. Aim for continuous improvement. Take into account the learning curve of advanced analytics. Set goals, review them, adjust them and keep working. Do you consider your data a resource or an asset? The era of "time is money" has come to an end. Today data is gold and big data analytics is the vehicle to turn the golden dream of the business future into reality. What is yours? Related posts: BI analysis of customer trends and behavior The future of the tourism sector depends on Big Data Top Five Big Data Applications.