In order to bring in more effective data management solutions you will need to know and follow the leading trends followed in it. This will save your from years of efforts that you need to put in to bring in the substantive changes. With the use of these latest trends some companies are moving faster than others while others who are not are stuck in between fits and starts finding least chances to move ahead.
Some of the most significant trends noticed in 2018 that carried forward to 2019 and has become even better are:
- Advanced analytics
- Ease of use incorporating Artificial Intelligence and machine learning
- Business Intelligence and Business Analytics prominence and
- Use of data catalogs.
All these help in accelerating decisions and at the same time it boosts productivity for any business irrespective of its type, size and market geologic.
For example, consider how the assimilation of data lakes and Hadoop shot forward but soon it was stalled once the users learned about the issues in its design and platform. It warranted them to backtrack it to get the issues fixed.
If you consider the other trends you will find that most of these are more localized. For example you can consider:
- The fruition of data semantics past metadata toward data cataloging
- Big data that recently attained mainstream prestige and enterprise integration in countless organizations and
- The churning up of the old big data by the onslaught of the new big data coming from the Internet of Things, IoT.
However, these happened to be the slowest yet most largely influential trend that resulted in using cloud as the most preferred computing platform not only for data but in fact for everything.
Take a look at all these as well as all other trends to decide which one to follow in 2019 so that you can stay within and well ahead in the race and excel just like RemoteDBA.
The 2018 major events
In order to know the merging trends you will need to consider the ones that it evolved from or the ones that stalled giving rise to an entirely new trend.
- The Hadoop hype: The halt of Hadoop is considered to be one of the biggest surprises of the recent times. Coming out from nowhere in 2013 and resulting in the production of more than one fifth of data warehouse settings 2016, it started to slow down in 2017 and almost came to a halt in 2018. This is because Hadoop had saturated progressive warehouse programs that were required. Moreover the users were dissatisfied with it immaturity with metadata management, relational functions, and platform maintenance part from its large on-site clusters and high cost. All these downsides ask for an immediate and extensive modernization.
- Data Lake adoption: Another major event in the recent past is the sudden adoption of data lakes that appeared in 2016. This is a design pattern and not a data platform like Hadoop. It offered useful methods for managing and manipulating data on big data platforms. In fact, most of the business owners retrofitted data lake methods to Hadoop implementations to manage data better and gain more business value. However, this too lacked in relational techniques with big data giving rise to the shift towards relational data lake found in relational database.
- Improved metadata management: This time also saw improvement in modern metadata management. This is a powerful enabler for all critical missions for the data driven businesses such as their operations and analytics. It improved with better automation that is primarily based on machine learning to keep up with the pace of the changing business necessities. With smarter data scanning it helped in leveraging new technologies to facilitate automation in the modern metadata management tools.
With big data becoming conventional and IT becoming cloudier it affected data structure deduction and source to target mappings automatically. It required new cloud based applications for support along with far better data platforms and more improved and effective virtualization techniques across clouds, on site or Software-As-A-Service applications.
While metadata still happens to be the most common approach to data semantics, it still requires a new approach called the data catalog.
Hot trends of 2019
All these paved the path for the most anticipated hot spots and trends of 2019 that will make data management faster, simpler and more effective.
- Hadoop Modernization: This improved the value of Hadoop enabling better data warehousing and analysis to gain more value form the business. Though people still continue to use Hadoop tools from the Apache ecosystem it is expected that more and more people will soon swap to Hadoop Distributed File System to store more cloud based objects.
- Data Lake Remix: The latest trend with data lakes is to build a multiplatform architecture. Just as with data warehousing, this will give the data a better and a larger ‘home.’ It will help the lake to be effectively distributed across all Hadoop clusters physically enabling the relational databases to be deployed on premises or on a cloud platform and even on any hybrid combination of both of these. This in turn makes the virtualization techniques required and handy in order to make disparate and varied data look much simpler than it actually is.
- Data Catalog: This helps in describing the different traits of data that include quality, its lineage, its domain, and profile statistics of any specific set of data. These traits being subjective raise the level of trust, sensitivity, compliance and usability when the users tag the available data to the score.
- IoT: IoT is the next wave of big data which is actually a computing paradigm. You can see a wide and most diverse range of physical devices such as vehicles, smart phones, shipping palettes, manufacturing robots, kitchen appliances, and lots of things that are fitted with a sensor. These things can transmit data about its state, location, surroundings, and activity.
Therefore, it can be concluded that the latest trends in data management is beneficial for both consumers and businesses and here to stay and change continually.
Andrew Thompson is a well-known blogger who is also an expert consultant in WordPress web development and database design. He used to write articles at RemoteDBA to help the newbie developers about smart methods in CMS based development and database management. To follow on Twitter