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Company Data Company Data

What Is Company Data?

Company data is information on the company’s aspects, interests, and inclinations. This is not just internal data like sales stats or customer relationships but also external data about the industry, location, company size, and customer behavior.

Where Does Company Data Come From?

Company data primarily comes from internal information from the company itself. This includes customer information, company performance statistics, software, assets, manuals and designs, financial information, and all other data in the company IT Systems or in an acquired company’s databases. Much of this information, however, can come from secondary sources like the data vendors for review on our site.

What Types of Columns/Attributes Should I Expect When Working with This Data?

All Database Management Systems (DBMSs) run by companies consist of one or more system-defined (i.e., built-in) simple data types. Two basic DBMS operators support extra operators for simple data types, including decimal, numeric, float, real, int, samllint, tintyint, char, and varchar.

These datasets also include information about subjects like employee performance reviews to lists of leads, transactions records, target markets, and product catalog data. Finally, many company datasets include information about business processes such as business goals or supply chain operations.

What Is This Data Used For?

Due to the broad array of information it contains, company data helps you make better business decisions at every level. Additionally, by bringing to light the weak points in your own organization and your competitors, you can make better long- and short-term decisions.

How Should I Test the Quality of Company Data?

To test the quality of your company data, consider the issues of accessibility, usability, reliability, consistency, and completeness. In other words, ask yourself questions like the following:

  • How available and accessible is the data?
  • How fast can it be accessed?
  • Is the dataset well structured, in a way that can be easily consumed?
  • How consistent is the dataset over time?

What Are the Most Important Factors I Should Vet When Working with This Data?

How data is gathered and analyzed depends on the intended use and on the nature and size of the organization. Further, data collection must comply with company and industry codes as well FOIA and other Privacy Protection legislation. In this vein (and in the interest of effectiveness and efficiency), only data that can shed light on company issues or opportunities should be collected.

The next step in vetting this data is an internal and external assessment of the company’s organization and goals. After this, the databases themselves can be evaluated for the short term or the long term as resource allocation is different for each.

Interesting Case Studies and Blogs to Look Into

Data Flair: 5 Big Data Case Studies – How big companies use Big Data
Sisense: Crunchbase Gets Access to the Right Data Across the Organization

Tangible Examples of Impact

Absa uses data analytics and data science models, combined with basic customer data and other data sets and variables, to pre-empt customer behavior and identify new customer needs. [Absa’s] ambition is to become a digitally led bank that is centred around the customer.

Absa Data Analytics Team wins International Award

Relevant datasets

PrivCo Enterprise Service

by PrivCo

PrivCo Enterprise Service provides a wealth of company financial data. They also deliver custom services and specially requested data

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Bureau Van Dijk – Catalyst

by Bureau_van_Dijk

Bureau Van Dijk Catalyst provides custom-built platforms for specific functions that integrate internal company data. In addition to platforms that measure credit, procurement, compliance, and M&A, they also provide other functions. These include Walletsizing, which assesses corporate banking wallets, Classification for regulatory checks, and TP for transfer pricing analysis. Interested users can download brochures on these products or take advantage of a free trial.

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Quandl Alternative Data

by Quandl_logo

Quandl Alternative Data caters to institutions like investors, publishers, universities, and more. Their alpha-generating datasets include company hiring activity, aviation intelligence, forex, and other data.

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