Data Analytics Progresses All Markets

Data Analytics Progresses All Markets

A growing value of and need for data analytics is apparent from an increased demand for data scientists in all industries, as well as more and more business leaders expecting information-driven decision making and business insight that relies on the masses of data being collected. This year, advances in data analytics could begin to influence organizations in new and innovative ways previously not considered and help further digital transformation and overall performance management.

What We Can Expect from Data Analytics Going Forward

With the speed of changes in big data increasing, data analytics is forced to keep up to ensure the most relevant insights are attained as quickly as possible. Experts suggest data preparation processes may provide challenges, but businesses that implement robust preparation strategies could reap the rewards of greater efficiency, superior decision-making, and increased profits. With far more sources of data available, data scientists aren’t faced only with ‘superfluous ingredients’ but are also facing the challenges of data quality; and data movement and management can be a significant difficulty too. For these reasons and more, we’re likely to see a growth in data preparation software helping users handle the growing data surge.

Another potential growth area in the coming months is streaming data analytics. An exciting prospect, again ensuring swift business engagement, but a formidable project for those responsible for the IT infrastructures that support such analytics, as well as the teams handling the final analysis of such data. Streaming analytics systems require advanced technical knowledge able to connect a range of analytics tools, big data platforms, and data processing technologies, and with a surplus of open source processing engines contending for the top position, IT technicians and data analysts have an overwhelming number of factors to consider. However, many large organizations already besieged with data are building up their IT resources to ensure investment and utilization of real-time analytics technology guarantee they’re able to take best advantage of the trend.

Artificial intelligence is already making waves this year, a technology that’s been quietly but confidently progressing in the past. This year, Machine Learning is likely to play a major role in the advancement of data analytics with industry experts pointing to applications for high volume repetitive tasks as a high value employment. We can also expect greater microservices impact with the integration of machine learning as applications leverage big data and make use of both past and streaming data for stronger insights.

Fresh Applications for Data Analytics

It’s unlikely data analytics will be excluded from any area for too long, but right now advances are being made into a few distinctive sectors. Some restaurants are making use of information that might once have been considered superfluous, sending ordering data to the cloud for analysis; such exploration is assisting with menu decisions, meal costings, and customer satisfaction. And in the very different area of law enforcement, data analytics is being implemented for improved crime fighting. Another sector with stacks of information, many law enforcement departments wouldn’t know how to begin effective data management, let alone gleaning valuable insights from the analysis of it, but developers are finding new ways to help such services better protect their communities with data analytics programs.

Data and data analytics are recognized in the global business market as worthwhile commodities, and the developers supporting the industry seem never to rest. Intel’s acceleration library, Data Analytics Acceleration Library, is just one of many notable tools progressing the field, and an interesting phenomenon being seen is with regards to the masses of open source tools becoming available. But don’t be too quick to fire your data specialists or service providers; this is a field wherein the value of the application is matched only by the skill of specialist operators.

By Jennifer Klostermann

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