Bạn đang xem: Top 5 data migration trends
It’s rare, if not impossible, lớn find a business that does not have a digital presence. The convenience factor of digital is accelerating the pace at which businesses are applying an online presence, including the ones that were mainly brick-and-mortar before COVID. More than just offering products và services in this way, most organizations are using data lớn generate insights that can affect their revenue, sales, cost, and business decision-making.
While being data- and insights-driven is a major focus for all CIOs and CDOs, that’s easier said that done. Without properdata management, and a related infrastructure in place, delivering trusted and good-quality data lớn stakeholders, both internal & external, is challenging. Lớn solve those problems, the data management industry is constantly pushing the envelope with many innovations related to lớn cloud, financial operations, newer data management architectures, automation, machine learning, etc. Here are the vị trí cao nhất five trends that we believe will have the most impact in 2023, as it related to data & analytics.
Trend #1: As recession looms, companies will look khổng lồ optimize infrastructure cost
Whether North America is in recession or not, companies are actively cutting costs, and reducing IT infrastructure, which has always been an easy choice for CEOs. While compute & storage costs continue khổng lồ be reduced through theusage of cloud, it still can lead to lớn huge bills for organizations given their heavy investments in data & analytics infrastructure. Thanks in part to lớn the breadth of choices of storage, compute, và applications, companies often take a rip-and-replace strategy to modernize their data và analytics efforts. That approach is not only costly, but it can often lead to disruption in IT operations. In 2023, more companies will see IT focusing on modern, non-disruptive ways to lớn update their IT infrastructure, whether their data resides entirely in one cloud, multiple clouds, or in a hybrid environment including on-premises.
Trend #2: While multi-cloud gets real, FinOps in cloud becomes necessary
For many companies, strategic data assets are spread across multiple clouds and geographical locations, whether that is because various business units or locations have their preferred cloud service provider (CSP), or because merger và acquisitions have led these assets to reside in different cloud providers’ boundaries. As more data continues to lớn move to the cloud, và different geographies see prominence of certain cloud providers vs. The others, there is accelerated adoption of multi-cloud architecture for multinational corporations. Currently, there is no easy way to manage và integrate data và services across these different CSPs. Failure to address this problem always results in data silos & a fragmented approach khổng lồ data management, leading lớn data access và data governance complications.
Also, contrary to lớn popular belief, cloud costs are increasingly becoming a material expense due khổng lồ the sheer volume of data & related egress charges, lớn name a few. For many organizations, cloud investments bởi not deliver the economic and business benefits as intended. As a result, they are leveraging FinOpsto provide a framework for controlling cloud costs andusage, identify cost vs. Value, và understand ways khổng lồ optimally manage it across modern hybrid and multi-cloud environments. In the coming year, expect FinOps to gain momentum as a critical initiative khổng lồ help companies better manage their hybrid-cloud and multi-cloud spend.
Trend #3: Accelerated adoption of data fabric and data mesh
Over the past two decades, data management has gone through cycles of centralization vs. Decentralization, including databases, data warehouses, cloud data stores, data lakes, etc. While the debate over which approach is best has its own proponents và opponents, the last few years have proven that data is more distributed than centralized for most organizations. While there are numerous options for deploying enterprise data architecture, 2022 saw accelerated adoption of two data architectural approaches – data fabric và data mesh – to better manage & access the distributed data. While there is an inherent difference between the two, data fabric is a composable stack of data management technologies & data mesh is a process orientation for a distributed group of teams to manage enterprise data as they see fit. Both are critical khổng lồ enterprises that want to manage their data better. Easy access khổng lồ data and ensuring it’s governed và secure, is important lớn every data stakeholder – from data scientists all the way to lớn executives. After all, it is critical for dashboarding & reporting, advanced analytics, machine learning, and AI projects.
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Both data fabric và data mesh can play critical roles in enterprise-wide data access, integration, management, và delivery, when constructed properly with the right data infrastructure in place. So in 2023, expect a rapid increase in adoption of both architectural approaches within mid- lớn large-size enterprises.
Trend #4: Ethical AI becomes paramount as commercial adoption of AI-based decision-making increases
Companies across industries are accelerating the usage of AI for their data-based decision-making – whether it’s about social truyền thông platforms suppressing posts, connecting health care professionals with patients, or large wealth management banks granting credits lớn their kết thúc consumers. However, when artificial intelligence decides the end result, currently there is no way to lớn suppress the inherent bias in the algorithm. That is why emerging regulations such as the proposed EU Artificial Intelligence Act, and Canada’s Bill C-27 (which may become the Artificial Intelligence & Data Act if enacted), are starting to lớn put a regulatory framework around the use of AI in commercial organizations. These new regulations classify the risk of AI applications as unacceptable, high, medium, or low risk và prohibit or manage the use ofthese applications accordingly.
In 2023, organizations will need lớn be able to lớn comply with these proposed regulations, including ensuring privacy and data governance, algorithmic transparency, fairness and non-discrimination, accountability, & auditability. With this in mind, organizations have to implement their own frameworks to tư vấn ethical AI (e.g., guidelines for trustworthy AI, peer reviews frameworks, & AI ethics committees). As more & more companies put AI lớn work, ethical AI is bound khổng lồ become more important than ever in the coming year.
Trend #5: Augmentation of data quality, data preparation, metadata management, và analytics
While the kết thúc result of many data management efforts is to feed advanced analytics and tư vấn AI và ML efforts, proper data management itself is pivotal to an organizations’ success. Data is often being called the new oil, because data- & analytics-based insights are constantly propelling business innovation. As organizations accelerate their usage of data, it’s critical for companies to keep a close eye on data governance, data quality, & metadata management. Yet, with the growing amount of volume, variety, và velocity of data continues, these various aspects of data management have become too complex khổng lồ manage at scale. Consider the amount of time data scientists & data engineers spend finding & preparing the data, before they can start utilizing it. That is why augmented data management has recently been embraced by various data management vendors where, with the application of AI, organizations are able to lớn automate many data management tasks.
According to lớn some of the đứng đầu analyst firms, each layer of a data fabric – namely data ingestion, data processing, data orchestration, data governance, etc. – should have AI/ML baked into it, to automate each stage of the data management process. In 2023, augmented data management will find strong market traction, helping data management professionals focus on delivering data-driven insights rather than being held back with routine administrative tasks.
There are many more noteworthy innovations taking place in the data và related infrastructure software market, which includes innovations in DataOps,proliferation of continuous decision process lifecycle, data protection, data utilization, etc.We believe all these innovations will accelerate the pace of digital transformation và digital business in 2023 và beyond. We also believe that the last two lớn three years have definitely taught us that digital business is where the future lies.
