I was going through Wayne Eckerson blog and find really interesting about this article.
The top-down world. In the top-down world, source data is processed, refined, and stamped with a predefined data structure--typically a dimensional model--and then consumed by casual users using SQL-based reporting and analysis tools. In this domain, IT developers create data and semantic models so business users can get answers to known questions and executives can track performance of predefined metrics. Here, design precedes access. The top-down world also takes great pains to align data along conformed dimensions and deliver clean, accurate data. The goal is to deliver a consistent view of the business entities so users can spend their time making decisions instead of arguing about the origins and validity of data artifacts.
The under world. Creating a uniform view of the business from heterogeneous sets of data is not easy. It takes time, money, and patience, often more than most departmental heads and business analysts are willing to tolerate. They often abandon the top-down world for the underworld of spreadmarts and data shadow systems. Using whatever tools are readily available and cheap, these data hungry users create their own views of the business. Eventually, they spend more time collecting and integrating data than analyzing it, undermining their productivity and a consistent view of business information.
The bottom up world. The new analytical ecosystem brings these prodigal data users back into the fold. It carves out space within the enterprise environment for true ad hoc exploration and promotes the rapid development of analytical applications using in-memory departmental tools. In a bottom-up environment, users can't anticipate the questions they will ask on a daily or weekly basis or the data they'll need to answer those questions. Often, the data they need doesn't yet exist in the data warehouse.
The new analytical ecosystem creates analytical sandboxes that let power users explore corporate and local data on their own terms. These sandboxes include Hadoop, virtual partitions inside a data warehouse, and specialized analytical databases that offload data or analytical processing from the data warehouse or handle new untapped sources of data, such as Web logs or machine data. The new environment also gives department heads the ability to create and consume dashboards built with in-memory visualization tools that point both to a corporate data warehouse and other independent sources.
Combining top-down and bottom-up worlds is not easy. BI professionals need to assiduously guard data semantics while opening access to data. For their part, business users need to commit to adhering to corporate data standards in exchange for getting the keys to the kingdom. To succeed, organizations need robust data governance programs and lots of communication among all parties.
Summary. The Big Data revolution brings major enhancements to the BI landscape. First and foremost, it introduces new technologies, such as Hadoop, that make it possible for organizations to cost-effectively consume and analyze large volumes of semi-structured data. Second, it complements traditional top-down data delivery methods with more flexible, bottom-up approaches that promote ad hoc exploration and rapid application development.
The top-down world. In the top-down world, source data is processed, refined, and stamped with a predefined data structure--typically a dimensional model--and then consumed by casual users using SQL-based reporting and analysis tools. In this domain, IT developers create data and semantic models so business users can get answers to known questions and executives can track performance of predefined metrics. Here, design precedes access. The top-down world also takes great pains to align data along conformed dimensions and deliver clean, accurate data. The goal is to deliver a consistent view of the business entities so users can spend their time making decisions instead of arguing about the origins and validity of data artifacts.
The under world. Creating a uniform view of the business from heterogeneous sets of data is not easy. It takes time, money, and patience, often more than most departmental heads and business analysts are willing to tolerate. They often abandon the top-down world for the underworld of spreadmarts and data shadow systems. Using whatever tools are readily available and cheap, these data hungry users create their own views of the business. Eventually, they spend more time collecting and integrating data than analyzing it, undermining their productivity and a consistent view of business information.
The bottom up world. The new analytical ecosystem brings these prodigal data users back into the fold. It carves out space within the enterprise environment for true ad hoc exploration and promotes the rapid development of analytical applications using in-memory departmental tools. In a bottom-up environment, users can't anticipate the questions they will ask on a daily or weekly basis or the data they'll need to answer those questions. Often, the data they need doesn't yet exist in the data warehouse.
The new analytical ecosystem creates analytical sandboxes that let power users explore corporate and local data on their own terms. These sandboxes include Hadoop, virtual partitions inside a data warehouse, and specialized analytical databases that offload data or analytical processing from the data warehouse or handle new untapped sources of data, such as Web logs or machine data. The new environment also gives department heads the ability to create and consume dashboards built with in-memory visualization tools that point both to a corporate data warehouse and other independent sources.
Combining top-down and bottom-up worlds is not easy. BI professionals need to assiduously guard data semantics while opening access to data. For their part, business users need to commit to adhering to corporate data standards in exchange for getting the keys to the kingdom. To succeed, organizations need robust data governance programs and lots of communication among all parties.
Summary. The Big Data revolution brings major enhancements to the BI landscape. First and foremost, it introduces new technologies, such as Hadoop, that make it possible for organizations to cost-effectively consume and analyze large volumes of semi-structured data. Second, it complements traditional top-down data delivery methods with more flexible, bottom-up approaches that promote ad hoc exploration and rapid application development.
No comments:
Post a Comment