Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    image fx (60)
    Data Analytics Driving the Modern E-commerce Warehouse
    13 Min Read
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: The data and information puzzle
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Warehousing > The data and information puzzle
Data Warehousing

The data and information puzzle

TeradataAusNZ
TeradataAusNZ
5 Min Read
SHARE

Discussions about the meaning of data and information is not new, as data managers have debated the semantics of data, information, knowledge, wisdom for a long time!

Discussions about the meaning of data and information is not new, as data managers have debated the semantics of data, information, knowledge, wisdom for a long time!

A few years ago I was doing research on economics of information and I came across a book by Harrington, J. (1991) titled “Organisational structure and information technology”, published by Prentice Hall International. Harrington observed that data are facts and information is the consequence of interpretation. What is information to some is not to others. Moreover, it is the time and utility which transforms data into information. At a particular time a set of data is useful to the individual and can be described as information while at another time the same set of data may not have utility and therefore not information. The data itself has not changed in any way but the individual’s perception of that data changes in the context of time.

More Read

Google Uses Web Searches to Track Flu’s Spread
In-House vs. Outsourced Call Centers: What to Choose
Question Assumptions Before Initiating Big Data Projects
IBM Research has built a new nanoscale microscope capable of…
Dietrich acknowledged that some of what she and her fellow…

From an organisational point of view, data and information are driven by resource-driven paradigm and perception-driven paradigm. In the resource-driven paradigm, data is considered a corporate resource and is centrally managed. As described by Alec, corporate managers continually enhance and ‘ring-fence’ corporate data as part of the planning process with an expectation that it can be tapped at any time with the certainty of achieving a predictable value from it. Thus, the limits imposed on the organisation’s database are based upon the managers’ own perception of their value as information. On the other hand, the individual employees’ perception of their information widens because of their greater accessibility to the information across the enterprise. Hence, on the one hand, the value of information is limited by the boundaries drawn up by the managers, and on the other hand, expanded by the perceptions of the employees having access to the enterprise network of data. So, information is the consequence of a complex psychological process that transforms perceived data into usable thought inputs by using the skills of employees for the benefit of improved communication and organisational performance. Whichever theoretical framework is considered, Teradata provides support for both resource-driven and perception-driven paradigms by means of technologies, tools, applications and solutions.

In the context of the resource-driven paradigm, Teradata enables organisations to create and maintain a centralised repository of data in the enterprise data warehouse (EDW). The EDW as a corporate resource provides a single source of data on which decision makers throughout the enterprise can make educated decisions aligned with corporate strategy. In this way, the EDW combined with a cohesive data management strategy can support the vision and unify the organisation. Besides, the Teradata Enterprise Data Warehouse Roadmap is a visual planning model showing the alignment of enterprise strategic goals and objectives through a “food chain” to the supporting data in the enterprise data warehouse.

The perception-driven paradigm is supported by providing a range of business intelligence and analytical solutions. For example, at Teradata, we also recognise that the face of effective customer relationship management (CRM) is continuously changing. Beyond leveraging new communication channels, companies must also craft messages in unique ways to ensure they can penetrate the barrage of competitors’ messages to reach—and resonate with—their intended recipients. Teradata Customer Relationship Management (TRM) blends best-of-breed functionality with the latest technology and a clear understanding of the evolution of CRM to create a system that can help customer-facing employees communicate with customers in smarter, more innovative ways, across both traditional and emerging channels by leveraging enterprise data.

Teradata Meta Data Services (MDS) enhances business intelligence tools by allowing users to identify, consolidate, understand, manage and navigate technical, business and lineage metadata, and it provides facilities to integrate related metadata from other sources in effective ways.

Integrating enterprise data sources and aligning with corporate goals can be a complex task, but realising value from it can be fun too! Try shaping the enterprise model by doing this little puzzle!.

Sundara Raman

 

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

image fx (60)
How Finance & BI Teams Choose Accounting Software
Big Data Business Intelligence Exclusive
Why the AI Race Is Being Decided at the Dataset Level
Why the AI Race Is Being Decided at the Dataset Level
Artificial Intelligence Big Data Exclusive
image fx (60)
Data Analytics Driving the Modern E-commerce Warehouse
Analytics Big Data Exclusive
ai for building crypto banks
Building Your Own Crypto Bank with AI
Blockchain Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Using Analytics in Tough Times: Quiet action starts the fight against “doom and gloom”

3 Min Read

Apple’s iLife ‘09 software suite will include a…

1 Min Read
Microsoft Access
Big DataData ManagementData Warehousing

Opportunities with Merging Microsoft Access With Big Data

5 Min Read

Some thoughts on advanced analytics in 2010

5 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?