Big Data & Digital Marketing

A key topic when trying to leverage Big Data is data integration.

Data integration can take long time and is crucial to really benefit from big data.

Silo breaking, made possible by data integration, is what can let a company move from applying short-term tactics to creating a long-term strategy.

It goes without saying that without some good questions (i.e. business objectives) even good data integration is of little use.

One good suggestion for defining the goal is to put the customer in the center, for real.

8 basic question to help you get started on the right track:

1. Who is your customer?

2. What do they need?

3. What data should you be looking for to see if you are delivering?

4. Where is the data coming from?

5. How is it stored/organized?

6. Who looks at it and how often?

7. Who is analyzing it?

8. Who is presenting it?

Five mistakes to avoid to fail a big data project:

1. Going at Big Data alone

2. Using outdated data management practices

3. Ignoring Big Data best practices

4. Failing to understand the importance of Big Data governance

5. Understanding the power of Big Data, aka concentrating at the finger and missing the moon.

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

Data Lakes as the Big Data alternative to Data Warehouses.

Their main features are:

1. Contain ALL of the data, both structured and unstructured, internal and external;

2. Store all data in RAW format;

3. No SCHEMA is imposed on the data.

I like Data Lakes because they:

1. Are flexible

2. Break silos

This increases the success rate of Big Data projects.

Nowadays, companies in virtually any field have the capability to gather, store and take advantage of massive amounts of information.But not all of them have the capability to manage the data in the proper way.
Here are 5 signs that it could be time to outsource your data management:1. Overpriced in-house management costs.2. Lack of in-house Big Data management experts.3. Constant need to re-deploy employees to do other tasks.4. Inability to comply with regulatory requirements.5. Failure to respond quickly to technological changes.
Avoid creating strong dependency on the third party expert and keep in mind these three things that can massively help you:1. Have a clear plan on how you want to use the data2. Embrace cloud technologies3. Develop in-house skills