Big Data & Digital Marketing

Data is certainly growing at an exponential rate, and the Internet Of Things is just making the process stronger. However, the buzz has created some false myths that need to be busted.

Five biggest myths about big Data:

1. The Entire Data is Accessible

2. Entire Data is Needed

3. Offers Certainty

4. Big Data isn't Here to Stay

5. Granular Data is Better

Big Data can be extremely dangerous without a Big Brain to analyse them properly.

Huge data sets ALWAYS contain some relations: some of them are right (causation), others are simply wrong. It pertains to data analysis to uncover the truth.

"As we move into an era in which personal devices are seen as proxies for public needs, we run the risk that already existing inequities will be further entrenched.

[...]

This goes beyond merely conducting focus groups to confirm what you already want to see in a big data set. It means complementing data sources with rigorous qualitative research."

As organizations become more and more data-driven, it becomes progressively more important to set up a healthy and productive way to manage data.

Here are 4 major steps to follow to help you improve on this:

1. Data Management

2. Data Security

3. Data Quality

4. The Team

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1.

Data management is the “administrative process by which the required data is acquired, validated, stored, protected, and processed, and by which its accessibility, reliability, and timeliness is ensured to satisfy the needs of the data users.”Basic pillars are: provisioning, protection, replication and recovery.Evaluate data before engaging in big data analytics.Have a maintenance plan.
2.

Data security must be prioritized by any organization to enable it to function properly and for operations to flow efficiently. It also provides stockholders and executive teams peace of mind of knowing that the information they have stored in their servers will not be easily exploited by hackers or cyber-criminals.
3.

A study conducted by Experian Data Quality shows that outstanding data quality has a direct correlation to an increase in company profits. 4 steps to reduce incidence of human error (cited by 65 percent of organizations to be the main cause of data problems): Identify data entry points, train staff, Automated verification, clean data over time.
4.

Hire a competent team of professionals who know their roles very well: data management supervisor, data entry staff, data analyst, quality and training staff

MetLife, British Airways and Tivo Research Analytics give their best suggestions:

1. The Plan
Set a clear plan with reliable goals, keep it simple and short term.

2. Use The Right Data
There 's a lot of data out there, select the right mix for your needs

3. Don't Create A Black Box
At the end of the day a Big Data project needs to give understandable insights. There are still CEOs and CMOs who want to know where the customers are and the CFO wants to know whether there's a return on the investment.