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Top Forecasts for Big Data in the Enterprise in 2019

Friday, June 7, 2019   (0 Comments)
Posted by: Kaylin Berg
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Softweb Solutions team


Big data analytics is the most dynamic and advanced segment of the IT industry. We have witnessed the importance of data collection and analysis in recent years. Data is like the fuel that runs the vehicle of digital innovation. And it is quite challenging to extract useful insights from the collected data. Hence, organizations need specific solutions to handle data challenges to get the benefits of digital innovation.

Artificial intelligence (AI) depends and flourishes upon big data, and it has now become the core of almost all the revolutionizing applications which are disrupting the existing landscape.

Big data consulting services providers can help to make your data simple to access and understand while helping you improve your data-driven business outcomes.

As a leader in the sector, IBM scientists break big data into four dimensions: Volume, Velocity, Variety and Veracity.


Let’s talk about the trends that the year ahead holds for big data:

AI will facilitate explainability

AI and ML algorithms help in analyzing data and extracting useful insights from it. And many enterprises are using them now. So there is more focus on transparency and explain-ability. For example, if a bank denies mortgage to a particular person, it does not prove that it was not denied on the basis of some illegal or irrelevant factor like race or gender. But with AI and ML algorithms in the system, the actual reason for denying the loan can be stated. And for that, the following requirements need to be fulfilled:

1. To have such transparency and explainability, we need to have:

  • appropriate data
  • relevant documents and quality data

2. To explain the model and use it properly for legal operations, it’s important to know:

  • where the data is captured from
  • what the data means


 More focus on hybrid environments

Moving to the hybrid cloud will be a big undertaking. But in the year 2019, the hybrid cloud cannot be ignored. The communications service providers will find out what they want and what they don’t want on the cloud. And they will build a roadmap based on business values and not functionalities.

Organizations are now more comfortable with hybrid environments. This is because a heterogeneous data estate includes multiple fit-for-purpose big data, relational, and NoSQL data stores, on-premises and in the cloud.


Machine learning (ML) will be used more in the mainstream

The year ahead holds a lot in terms of technological innovations and transformations. Organizations will be using ML to develop operational analytics pipelines and the usual stream of their business processes.

There are two specific developments that are speeding-up the applications of ML:

  • The ‘citizen data scientist' who can use the elementary ML algorithms in their data pipelines
  • The ability for data scientists to use more automated tools to put advanced ML algorithms into production.

This will make a big difference in 2019 because the automation frameworks will enable data scientists to create their own data pipelines. And those data pipelines will be almost ready for production. Combining data engineering with data scientists and data science with data analytics will increase ML algorithms that would go into enterprise-level production.


Deep learning gets deeper

Deep learning has proved its strength through its initial uses in computer vision and natural language processing (NLP). Organizations will now develop deep learning more and explore innovative methods for its implementation. Big financial institutions have already used it and realized that neural network algorithms are more efficient in detecting fraudulent activities as compared to the traditional methods of practice. And hence they will explore it further and generate more such uses of deep learning in the coming year.


Database as a Service

The providers of Database-as-a-Service will cater to the dynamic needs of the clients in the future. And hence, they will embrace the big data analytics solutions in the coming years. Organizations are already collecting data from all the relevant sources. They now seek new ways to filter the data efficiently for using it in a more productive manner.


The final say

The year 2019 will be a year of progress at every front. Organizations will be able to find the right data and create the right features. And they will use it to create dependable models for making the applications functional and useful. AI and ML have a big role to play in exploring and understanding the data required to create those models. And despite certain hurdles, the potential benefits of big data analytics will not be ignored.

Learn more from the Softweb Solutions team here

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