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How to take care of your 5 major data challenges

5 key data challenges

1. Massive data growth- follow analytics, manage your data

Data is getting bigger and complicated every day. Data growth is one of the top challenges now. In a typical B2B scenario your organization is in need of consistent, reliable, and manageable data. In a customer-centric era, clean, error-free data is the key to building a successful customer relation. An effective data provides a customer’s insight more efficiently.

2. Data protection

Storing and protecting your data is one of the major concerns. As volume of data increases, managing enormous data becomes a challenge. It brings other loopholes along with it. Lack of security, adherence to growing number of compliances and quality management are reasons. Cloud computing offers an attractive choice for managing customer data due to its’ cost effectiveness, speed, and greater accessibility. Your organization can decide, who can create, access, share or analyze customer data.

3. Meeting speed

In a hypercompetitive market it is most important for you to maintain top speed. You, not only need to analyze relevant data but also find them quickly. An active visualization helps your organization analyze relevant data and make decisions quickly and effectively. In the 'big data' era, managing large volumes of data and accessing it at an equally high speed is a challenge. These challenges grow as degree of granularity increases. One possible solution is keeping the right type of infrastructure including hardware.

4. Cleaning Data

Growth of your organization is surely dependent on collection of clean, non–redundant and relevant data. You need to maintain quality data, increase productivity with clean and relevant data. Do a data revamp, win back your old customers? Process of collecting data from multiple sources can become complicated. Assessing quality of data and consistency can become more challenging at times. It is difficult to harness effective data for growth of your organization.

There are several processes that help you cleaning erroneous data.

These are given as following:

  • Parsing(for the syntax error)
  • Error correction and loss of information (remove invalid entries)
  • Maintenance of clean data(to stop repeated re-cleansing)

5. Understanding your data

It is important for you to understand data you are using. Do segmentation before using data. Prioritize your customer. There are several types of data which you gather from multiple sources. This data help you to segment your potential customer in various groups based on factors like type, geographic location, buying habits and so on. Segmentation of this data to understand your potential customer is one of the key challenges and equally a boon.It helps you to communicate to your customer at a much deeper level.

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