Five big data challenges that companies face

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Creating and successfully executing a big data strategy has the potential to be genuinely transformative; however, there are a number of challenges that organisations can face when it comes to big data. Let’s look at five of these.

1. Managing large amounts of data

By its very nature, big data is large and complex. It also tends to be held on different platforms/systems that are not necessarily compatible. One of the first challenges is to create a big data architecture that can consolidate all the data sets from various sources.

2. Evaluating and choosing technologies

This can prove challenging, as technologies can often overlap and it can be hard to pinpoint which ones are best for a particular organisation. There are many that incorporate AI and machine learning. A choice also needs to be made as to where the data is processed

3. Data quality issues

There is often a considerable variance in the quality of data on different systems. Poor-quality data can generate false/misleading results; therefore, a key challenge for any company is the need to constantly monitor and fix data quality issues as they are discovered. AI tools can potentially help with this.

If you feel that your organisation could benefit from the help of a data analysis company, there are plenty of companies that specialise in this. A number of these, such as https://shepper.com/, have useful online resources.

4. Data integration complexities/strategy

As datasets are constantly being updated and added to, companies must have access to all data sources all the time. Collating data in a central repository such as a data lake is a common choice, but the integration can be a challenge. A strategic rather than ad-hoc approach is best.

5. Scaling systems efficiently and effectively

It can be challenging to roll out a big data strategy across the wider organisation. Organisations must know in micro detail all the types of data they have and how they are used, stored, and processed. A data lake can certainly help enable the more efficient use and reuse of data.