Big Data Trends You Should Definitely Follow In 2019

Are you wondering which Big Data trends will be the hottest topics in 2019?
Here are some of the options:

Data retention policies

Companies will still need to hold on to data for a while but there will no longer be the need to store data forever. Machine learning can learn to clean and protect the data and consequently to erase any data that is either outdated or not being used anymore.

Organizations usually use an automated system, an archive software which securely deletes data without manual intervention and in proper time. But, the companies have to show that they only delete data that is not subject to laws and regulations. Various types of information should be held at a different amount of time, depending on the industry and company. Some companies have their own data retention policies but some of the global or federal data retention laws still have to be followed. For instance, the SOX data retention policy for all publicly traded companies in the US or HIPPA policy for all medical institutions.

However, the erased information will not be gone forever. In fact, the algorithms in machine learning will be able to serve you as backup and if you need some of the erased data, the algorithms can be used to recreate some of the data.

This will come in handy to many companies in the future.

Streaming IoT Machine Learning

Experts are currently trying to use IoT to combine Streaming Analytics and Machine Learning. In the next year, you can expect an advance in research of this subject matter and there is even a possibility of creating a few startups that will market their services or software related to this.

With this new model, streaming data will allow Machine learning to get data in real-time and in a less controlled environment from the IoT. The goal of this process is to create a more flexible response system on a wide variety of occasions with a focus on human interaction.

All of this requires complex algorithms. Machine learning will then train the system to predict more accurately. As this changes and adapts, models in the Cloud will match those changes.

More and more businesses will prefer data flow to data that just landed in the data base. The flows will capture key events. This will be used largely in the medical industry and tracking patients with chronic diseases in order to adapt the regime to their current state.

Data Curator

Experts say that in 2019 many employers will be looking for people to fill the position of a Data Curator. This role will involve managing and organizing metadata as well as protecting data, Data Governance and quality. Data Curators will not only work on managing and maintaining data but they will also have the responsibility of determining and developing best practices for working with that data. They will also be responsible for presentations and showing data visually so that everyone can easily comprehend what it means in the form of either a dashboard, a chart, a slideshow or something similar.

Data curator will have to work together with researchers and host training for everyone involved. They will also have to collaborate with other curators in order to coordinate – this is where good communication skills will come in handy.

They will have to understand analysis and the types of it that need to be used in different parts of the company, what datasets will work for each part and what it takes to take data from that raw state that doesn’t mean anything into the state where it can actually make a difference. They will use self-service platforms to speed the process up and provide data that consumers can access without making copies.

Predictive Analytics Tools

Predictive and prescriptive analytics is the most talked about trend of this and hopefully, the upcoming year. Big data is turning into the main focus of analytics for large companies and the small and medium businesses alike.

Predictive analytics is a process of getting information from datasets with the goal to predict probabilities – as the very name of it says. It’s a part of data mining which goes into only the past data. This includes estimated future data and this is why there is always a possibility of a mistake happening. It indicates what may happen in the future with the level of reliability being high enough to be acceptable. It also provides the businesses with different scenarios and the assessment of the risk involved. Predictive analytics takes in the current data and facts of history in order to understand all of the stakeholders and provide the company with risks and opportunities.

Prescriptive analytics, on the other hand, does something else – it goes further than that. Prescriptive analytics takes in data or content to make a statement what decisions companies should make and what they should do in order to get to their goals. It uses the techniques like simulations, complex event processing, machine learning and so on.
What it essentially does is try to see what the effect of those crucial decisions will be in order to change those decisions before you make them.

Digital Ethics and Privacy

Security is one of the biggest trends in the past few years because of all the cases where the data was breached or there were various data security issues like huge data losses – AOL, LinkedIn, JP Morgan Chase or Apple spring to mind.
The big enterprises are all over the news but small businesses are vulnerable to this too. All the talk about the data security will continue into 2019 and it will concern both the private and the public sector.

These have been some of the biggest Big Data trends that will follow us into the next year. It will definitely make for an interesting year.