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Source: ZE

Organizational silos are problematic because they can lead to informational discrepancies between business departments which operate independently of one another. Data silos are extremely detrimental for two main reasons: their inflexible composition limits the amount of sharable resources, and they induce high operating costs due to a need for additional management personnel and large amounts of time required for their upkeep.1

Industry and company-specific data is crucial for risk management and finance departments in particular, in order that they may obtain a holistic understanding of market trends and potential pitfalls. Certain types of data are incredibly volatile, and may frequently change or be affected by other factors- so it is important to implement a data collection mechanism that accounts for these possibilities. It is extremely inefficient for companies to rely on spreadsheets or insecure methods like email to distribute information; both methods are very vulnerable to human error, and neither enable a systematic way of conducting analysis. Without a robust, integrated data management system, it is challenging for departments to effectively compare, visualize, and share information.

The Importance of Data Management Solutions

In order to avoid the problems created by data silos, firms are turning to enterprise data management software. In 2013, New Vantage Partners surveyed top executives at Fortune 100 companies to gain insight into business investment in data. Results revealed that corporations have become keenly aware of the immense value master data management systems provide.2

Key Survey Findings:

  • 91% of corporations are planning a data initiative or currently have one underway
  • 60% of companies have at least one type of data system already implemented
  • 88% of executives estimate that their companies will spend more than $1 million on data by 2016

Implementing a system which assists with data aggregation is incredibly useful, but it may not fulfill all of the necessary components of a data management process–particularly the analytical requirements of risk managers. The various quantitative and qualitative risks facing energy, commodity, and financial markets are continuously growing, and so is the complexity of regulations in these industries. Simply having access to a data domain does not make compliance any easier; creating custom spreadsheets, deriving results, and making them interpretable can be a huge challenge.

ZEMA: Data Management Simplified

ZEMA offers a completely integrated data management solution that is specifically designed to eliminate issues regarding organizational and data silos.

ZEMA’s security layer enables users to create rules and monitor permissions for individuals or groups within all departments of an organization. This ensures that all necessary members of an organization have access to the same centralized information and increases organizational transparency.

With ZEMA, users can display various types of information on one screen. Employees can also upload customized spreadsheets, from which ZEMA can pull data to analyze results and offer custom display options. A combination of different types of information is shown on one screen to enable risk managers, traders, and analysts to contrast different types of content. The data analyses and manipulations created within ZEMA can be shared with different users and groups from an organization.

ZEMA not only breaks down barriers between different departments, but is also capable of analyzing complex data sets, building forward curves, and integrating information with downstream systems. To learn more about ZEMA, book a demo today.

Bibliography

1 Christensen, Kent. “Goodbye, Silos: The Benefits of Converged Data Centers.” Data Center Knowledge, August 14, 2012. http://www.datacenterknowledge.com/archives/2012/08/14/goodbye-silos-the-benefits-of-converged-data-centers/.

2 “New Vantage Big Data Executive Survey 2013: Business Adoption Backs up the Big Data Buzz.” September 9, 2013. http://newvantage.com/wp-content/uploads/2013/09/NVP-Big-Data-Press-Release-090913.pdf.