Data Analytics

Top 5 Data Analysis Trends in 2019

By December 28, 2018 June 13th, 2019 No Comments
Data Enrichment Enriched Data Data Enhancement Data Quality

As businesses transform into data-driven enterprises, data technologies and strategies need to start delivering value. Here are 5 data analytics trends to watch out for in 2019…

 

What makes data quality management the most important trend in 2019?

The internet is on the rise and so is the availability of big data collection techniques. These big data collection techniques are facilitated by different artificial intelligence software. Over the past year it has not just been about collection of data, rather more about the quality of the data and the context in which the data is interpreted and used, which serves as most crucial aspect of business analytics. Moreover, a survey conducted by Business Application Research Centre also states that data quality management is the most important trend of 2019.

 

How will data lakes survive in 2019?

Not long ago, storing and obtaining actionable insights from big data was difficult. Now, with data lakes, you can store everything in a single data repository and enterprise-wide data management for everything from business analytics to data monetization. However, while storing big data in one place has been beneficial, revealing insights from that data has been difficult. In order for the data lakes to survive in 2019, it will have to prove its ‘business value’ as Ken Hoang says. This could be done by changing the ways of presenting data thereby enabling decision makers to have a deeper insight.

 

R Language in Data Analytics

There are a variety of ways to analyze data using statistical tools and other similar methods, but the most effective is using tools that integrate with R language. R is one of the best and the easiest way to conduct advanced data analysis since it can be audited and rerun easily, unlike spreadsheet software. It also provides a wide range of statistical techniques, making it a trendsetter of 2019.

 

What is cloud storage and analysis?

Cloud computing is an efficient way of doing data analytics, in fact it is a mantra one should follow, otherwise your big data faces delays if it moves across a local network and even larger delays if goes through the internet. As the amount of data increases in your computer the capacity of your data center decreases. So, in order to cater to the big data, cloud storage should be added in your computer. Along with your big data, your analysis should be in cloud too. More and more companies are switching to cloud storage as the amount of data they collect continues to grow each and every day.

 

Why are mobile dashboards heating up?

In this fast-paced world with everyone on the go, data management tools need to present more mobile friendly dashboards that are useful and timely for business analytics. Since many business leaders hardly have the time to sit back at their desks, this business intelligence tool is very important. Most self service business intelligence tools have this capability, but not all do; hence this should be utmost priority for every business analytics platform.