Data is everywhere; it can give both an accurate insight and the fog of visibility at the same time. Over recent years, streaming data technologies has become the latest norm whether it’s through the internet of things (IoT), Mobile and Big Data Pipelines. Several businesses are found struggling to put better data management practices.
Unrelenting pressure from non-traditional players is seen driving organizations transform themselves digitally. Generating massive amounts of data from new sources is no longer a luxury; it has become a necessity Right from customer information to financial transaction, product and service purchase histories, customer journeys, marketing campaigns, service inquiries, market feeds, social media streams, Internet of Things (IoT) streams, software logs, and text messages (including emails and SMS), plus those newer sources, companies require capturing it all.
Although the data management landscape seems to have evolved in 2018, in 2019 it will be even more transformative. Let me show you why!
#1 Data protection and Data transparency
With increasing strong demands from end consumers, enterprises are seen accommodating improved data protection across platforms, social media channels, cloud applications and more. Day in day out, demand for transparency seem to have increased regarding how data is collected, aggregated and shared. To accomplish these goals in tandem, enterprises will need to adopt enhanced technology solutions that can better protect data, and deliver detailed reports to organizations and their customers about data usage.
#2 Automation, machine learning, and AI will abound
More and more organizations are seen emphasizing on the use of AI and machine learning technologies to improve data quality and data management processes. Although, certain companies are seen helping when it comes to scaling data management processes without adding substantially more staff. When paired with automation, advanced analytics will ease the burden of overworked data engineers and data stewards. The day has come where we are all set to make the most of technologies like natural language processing fit into broader enterprise data management and analytics projects, but many will struggle to see meaningful results.
#3 Time to play data defense and offense
With more and more data moving from on-premises to cloud locations, it turns out challenging for any organization is to cope with the governance. So what can be done? Businesses should be prepared for more laws centered on consumer data protection, with the associated changes to the technology needed to cope not far behind. As a result, it will be more critical for them to find the correct balance of offensive (being agile and exploratory with data and technology) and defensive (governance and control of data) approaches to solving data-centric problems.
#4 Blending advanced analytics with data management
Big data seems to have to take off in a big way like never before. This lead to increasing demand for data lake concepts that combine Hadoop Distributed File System infrastructure, event stream processing, relational and non-relational data stores, and other technologies.
General Data Management Trends
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We will see enterprises moving towards decentralized Data Governance from hierarchical Data Architectures.
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The tiered data storage method will be in vogue where different media are used for different types of data, will be commonplace in the coming year to optimize space usage and cost.
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GDPR will be put into practice across all data pipelines and Data Management platforms to ensure higher data privacy, security, and governance
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Hybrid solutions like private-public Cloud will be used for increased productivity and efficiency across organizations.
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Storage, Analytics, or BI such Data Management functions will be outsourced. It will save larger enterprises to save on-premises, data center costs.
