By: Risko Tiitso
Quality Data Improves Analysis

What is Big Data?

This data explosion is pushing enterprises in a more data- driven direction. Organizations are now performing complex analysis on their data. It helps them analyze the market trends, develop streamlined operations and enhance the customer experience.

Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.

Analytics projects generally start by bringing data from siloed data sources into the main system. Here, the quality of the data you put in directly affects the quality of the resulting analysis. That’s why it’s always a surprise when an organization doesn’t take data quality seriously.

Poor data quality initially poses no significant problems from a functional perspective. The data sources can still be brought into the analytics system, reports can be built and conclusions will be drawn. But what if these conclusions are all wrong? It’s essential that the conclusions we draw from data guide the organization’s strategy in a useful way. If the data is inaccurate, it ultimately influences the decisions that managers and directors are making.

Big Data – What Is It Good For?

The 3 D2D’s:

1) Data-to-Discovery

2) Data-to-Decisions

3) Data-to-Dollars (Dividends)

What Factors Create Data Quality Issues

The Costs of Poor Data Quality

Poor data quality costs the typical company at least 10% of revenue. 20-35% is probably a better estimate.

Ways to Improve Data Quality

  1. Improve data collection
  2. Data profiling
  3. Improve data organization
  4. Cleanse data regularly
  5. Normalize your data
  6. Data quality firewall
  7. Integrate data across departments
  8. Segment data for analysis

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Categories: Finance & Controlling