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	<title>cloud data Archives - CDInsights</title>
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		<title>Data Reliability Engineering: You Can’t Fly Blind in the Clouds</title>
		<link>https://www.clouddatainsights.com/data-reliability-engineering-you-cant-fly-blind-in-the-clouds/</link>
					<comments>https://www.clouddatainsights.com/data-reliability-engineering-you-cant-fly-blind-in-the-clouds/#respond</comments>
		
		<dc:creator><![CDATA[Salvatore Salamone]]></dc:creator>
		<pubDate>Wed, 03 May 2023 20:31:00 +0000</pubDate>
				<category><![CDATA[Cloud Data Platforms]]></category>
		<category><![CDATA[Governance]]></category>
		<category><![CDATA[Sponsored]]></category>
		<category><![CDATA[cloud data]]></category>
		<category><![CDATA[data reliability]]></category>
		<guid isPermaLink="false">https://www.clouddatainsights.com/?p=2579</guid>

					<description><![CDATA[Borrowing from SRE and DevOps and bringing data into the fold just as these groups did with infrastructure and applications, data reliability engineering is the practice of delivering high data availability and quality.]]></description>
										<content:encoded><![CDATA[<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><img fetchpriority="high" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2023/03/data-reliability-2-Depositphotos_36009043_S.jpg" alt="" class="wp-image-2581" width="755" height="527" srcset="https://www.clouddatainsights.com/wp-content/uploads/2023/03/data-reliability-2-Depositphotos_36009043_S.jpg 1006w, https://www.clouddatainsights.com/wp-content/uploads/2023/03/data-reliability-2-Depositphotos_36009043_S-300x210.jpg 300w, https://www.clouddatainsights.com/wp-content/uploads/2023/03/data-reliability-2-Depositphotos_36009043_S-768x537.jpg 768w" sizes="(max-width: 755px) 100vw, 755px" /><figcaption class="wp-element-caption"><em>Borrowing from SRE and DevOps and bringing data into the fold just as these groups did with infrastructure and applications, data reliability engineering is the practice of delivering high data availability and quality.</em></figcaption></figure></div>


<p>While companies are transforming their workloads to hybrid and multi-cloud environments, they still treat operations as silos between infrastructure, applications, and data. To manage the complexity with a resilient, reliable, secure, and cost-optimized approach, organizations need all three to go hand in hand.</p>



<p>Unfortunately, before that can happen, each of the areas must get equal treatment. And that has not been the case with data. Businesses have invested great amounts of time and money in planning, developing, testing, and deploying infrastructure and apps. But not as much attention has been paid to the data aspects of their operations.&nbsp;</p>



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<p>Why is this so important? There are multiple reasons.</p>



<p>Many businesses today aim to be data-driven. They make strategic decisions by analyzing the vast amounts of data available from numerous sources such as smart sensors, IoT devices, social networks, website clickstreams, customer interactions, and more. The sources and quantities of data are increasing as a result of the wide-scale embracement of digital transformation.</p>



<p>Inaccurate data and its lack of availability to needed data can impact business success or failure. A bank calculating a suitable rate for a loan applicant could lose a good customer or lock in a risky one if the data the analysis was based on is outdated or inaccurate.</p>



<p>Another factor that impacts data reliability is the complexity of modern applications. Cloud-based apps and workloads are often composed of modular elements and distributed systems and often make use of multiple data sources.</p>



<p>The complexity makes it hard to see the relationship between data and outcomes. An interesting example from the pandemic illustrates the point. Medium and short-term computer weather models <a href="https://www.washingtonpost.com/weather/2020/05/12/weather-forecasting-coronavirus-flights/">started having unusual inaccuracies</a> during the pandemic. It turns out model accuracy was aided by wind direction and speed, air pressure, temperature, and humidity measurements collected globally by commercial airlines and cargo planes. This was not obvious due to the expansiveness of the application and the data sources used as input. It took an extensive investigation to figure out what was happening.</p>



<p>Most businesses do not have the resources of government agencies to track down such data issues. Yet, their hybrid and multi-cloud applications and distributed data sources are just as complex.</p>



<p>These are areas where data reliability engineering can help.</p>



<h3 class="wp-block-heading">The emergence of data reliability engineering</h3>



<p>Historically, data issues were relegated to data engineers, data scientists, and analytics experts. These groups did not have the tools and processes at their disposal that&nbsp;other teams like SREs or DevOps already made use of in their respective infrastructure and application arenas. &nbsp;</p>



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<p>Thus emerged the need for a functional entity called data reliability engineering. Borrowing from SRE and DevOps and bringing data into the fold just as these groups did with infrastructure and applications, data reliability engineering is the practice of delivering high data availability and quality throughout the entire data life cycle from ingestion to end products.</p>



<p>A data reliability engineer (DRE) looks for errors in a company&#8217;s data operations, seeks to ensure data reliability and quality, and makes sure data pipelines are delivering fresh and high-quality data to the users and&nbsp;applications.</p>



<p>Additionally, by adopting Data Reliability Engineering (DRE) best practices, DREs can show the internal stakeholders data&#8217;s importance to the organization. And as is the case with SREs and DevOps, a DRE team should develop KPIs and metrics data for data availability, data completeness, and&nbsp;data downtime.</p>



<p>And also, just like SRE and DevOps, DREs must use a variety of tools and methodologies to be successful. For example, data observability tools can help provide visibility, identify data problems, optimize data usage and capacity planning, and help achieve data trust.</p>



<p>Additionally, there is a need for tools to automate&nbsp;data&nbsp;policies to guarantee data availability, reliability, and quality. Automation is also needed to identify root cause issues, self-correct problems, and self-heal data flaws to enable enterprises to move faster and reliably.</p>



<p><strong>See also:</strong> <a href="https://www.rtinsights.com/data-engineers-bad-data-two-days/" target="_blank" rel="noreferrer noopener">Data Engineers Spend Two Days Per Week Fixing Bad Data</a></p>



<h3 class="wp-block-heading">The need for a technology partner</h3>



<p>DRE is a critical but emerging field. It requires a variety of skills and tools and greatly benefits from proven best practices and topic area knowledge.</p>



<p>Unfortunately, many businesses find they do not have the internal expertise or resources to undertake DRE efforts. And as such, they seek the help of a partner.</p>



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<p>Increasingly, help is coming from organizations and providers that provide an integrated portfolio of cloud and application professional and managed services offerings designed to help businesses address the complexity of modern cloud infrastructure, application, and data environments.</p>



<p>Ideally, the partner needs a wealth of experience that is complemented by best practices shared with their clients. In some cases, a partner might have a center of excellence where accumulated knowledge and expertise are turned into well-honed playbooks, best practices, implementation guides, and more.</p>
<div class="saboxplugin-wrap" itemtype="http://schema.org/Person" itemscope itemprop="author"><div class="saboxplugin-tab"><div class="saboxplugin-gravatar"><img decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/05/sal-headshot-150x150-1.webp" width="100"  height="100" alt="" itemprop="image"></div><div class="saboxplugin-authorname"><a href="https://www.clouddatainsights.com/author/ssalamone/" class="vcard author" rel="author"><span class="fn">Salvatore Salamone</span></a></div><div class="saboxplugin-desc"><div itemprop="description"><p>Salvatore Salamone is a physicist by training who has been writing about science and information technology for more than 30 years. During that time, he has been a senior or executive editor at many industry-leading publications including High Technology, Network World, Byte Magazine, Data Communications, LAN Times, InternetWeek, Bio-IT World, and Lightwave, The Journal of Fiber Optics. He also is the author of three business technology books.</p>
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		<post-id xmlns="com-wordpress:feed-additions:1">2579</post-id>	</item>
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		<title>Cloud Database Security Market to Reach $27 Billion By 2028</title>
		<link>https://www.clouddatainsights.com/cloud-database-security-market-to-reach-27-billion-by-2028/</link>
					<comments>https://www.clouddatainsights.com/cloud-database-security-market-to-reach-27-billion-by-2028/#respond</comments>
		
		<dc:creator><![CDATA[David Curry]]></dc:creator>
		<pubDate>Fri, 29 Jul 2022 01:55:04 +0000</pubDate>
				<category><![CDATA[Security]]></category>
		<category><![CDATA[cloud data]]></category>
		<category><![CDATA[data privacy]]></category>
		<guid isPermaLink="false">https://www.clouddatainsights.com/?p=1476</guid>

					<description><![CDATA[Continued adoption of cloud database technologies, new regulations, and increased cyber threats are key drivers of the cloud security market.]]></description>
										<content:encoded><![CDATA[<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><img decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/07/cloud-security-Depositphotos_28872607_S.jpg" alt="" class="wp-image-1477" width="750" height="563" srcset="https://www.clouddatainsights.com/wp-content/uploads/2022/07/cloud-security-Depositphotos_28872607_S.jpg 1000w, https://www.clouddatainsights.com/wp-content/uploads/2022/07/cloud-security-Depositphotos_28872607_S-300x225.jpg 300w, https://www.clouddatainsights.com/wp-content/uploads/2022/07/cloud-security-Depositphotos_28872607_S-768x576.jpg 768w" sizes="(max-width: 750px) 100vw, 750px" /><figcaption>Continued adoption of cloud database technologies, new data privacy regulations, and increased cyber threats are key drivers of the cloud security market. </figcaption></figure></div>


<p>The cloud database security market is expected to reach $27 billion in market value by 2028 at a CAGR of 19% during the forecast period, <a href="https://www.emergenresearch.com/industry-report/cloud-database-security-market">according to business management consultancy Emergen Research</a>.&nbsp;</p>



<p>Continued adoption of cloud database technologies across all industries, especially healthcare, alongside the growing need for security to meet regulatory compliance and the increased threat of cyberattacks will be the key growers of the market.&nbsp;</p>



<p>Emergen Research also mentions increased use of mobile devices, especially across developing regions such as South-east Asia, as another factor in the growth of the market.&nbsp;</p>



<p><strong>See also:</strong> <a href="https://www.clouddatainsights.com/cloud-security-a-primer/" target="_blank" rel="noreferrer noopener">Cloud Security: A Primer</a></p>



<p>Alongside increased adoption, organizations are also offloading more data off premises than ever before. Where once organizations kept private details and other sensitive data in on-premises data servers, even these are now sometimes being handled in the cloud. </p>



<p>In countries where regulations on sensitive information and privacy are strict, organizations are having to invest heavily in cloud database security to avoid hefty fines for non-compliance. Some are having to adopt multiple different security policies to ensure global compliance.&nbsp;</p>



<p>This has elevated the need for cloud security across all organizations. In particular, Emergen Research highlights eHealth applications and the Banking, Financial Services and Insurance (BFSI) segment as two of the fastest growing industries for cloud security.&nbsp;</p>



<p>Emergen Research expects the hybrid cloud security to register a higher growth rate between 2020 to 2028, in comparison to public and private cloud. This is partly due to the majority of small and medium sized enterprises (SMEs) deploying some form of hybrid cloud solution, rather than sticking to one or the other.&nbsp;</p>



<p>The market is still quite fragmented, with cloud database providers having their own security solutions built into the product and third-party applications which can sit on top of the platform or protect critical end-points. </p>



<p>North America is the region that spends the most, accounting for 39.2 percent of revenue in 2020. That is expected to decline somewhat by 2028, with Europe being the fastest growing region during that period, however North America will still be the largest spender by region according to Emergen Research. </p>
<div class="saboxplugin-wrap" itemtype="http://schema.org/Person" itemscope itemprop="author"><div class="saboxplugin-tab"><div class="saboxplugin-gravatar"><img loading="lazy" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/05/curry-150x150-1.webp" width="100"  height="100" alt="" itemprop="image"></div><div class="saboxplugin-authorname"><a href="https://www.clouddatainsights.com/author/david-curry/" class="vcard author" rel="author"><span class="fn">David Curry</span></a></div><div class="saboxplugin-desc"><div itemprop="description"><div class="author-info">
<div class="author-description">
<p>David is a technology writer with several years experience covering all aspects of IoT, from technology to networks to security.</p>
</div>
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		<post-id xmlns="com-wordpress:feed-additions:1">1476</post-id>	</item>
		<item>
		<title>Why Data in the Cloud Will Soon Morph into Autonomous Distributed Data</title>
		<link>https://www.clouddatainsights.com/why-data-in-the-cloud-will-soon-morph-into-autonomous-distributed-data/</link>
					<comments>https://www.clouddatainsights.com/why-data-in-the-cloud-will-soon-morph-into-autonomous-distributed-data/#respond</comments>
		
		<dc:creator><![CDATA[David Linthicum]]></dc:creator>
		<pubDate>Wed, 25 May 2022 02:04:34 +0000</pubDate>
				<category><![CDATA[Cloud Data Platforms]]></category>
		<category><![CDATA[autonomous data]]></category>
		<category><![CDATA[cloud data]]></category>
		<guid isPermaLink="false">https://www.clouddatainsights.com/?p=1104</guid>

					<description><![CDATA[The autonomous data that’s coming soon will be a bit different from the structured and unstructured data of the present and past.  ]]></description>
										<content:encoded><![CDATA[
<p>Let’s say you want to share information with another company. There could be a wide variety of valid reasons to share information, such as sending inventory information to place an order from a vendor or report production details to support an external production audit. Let’s also say you plan to send thousands of pieces of data in the exchange.&nbsp;</p>



<p>Here’s the problem: Once the data is out of your control, you can no longer assume that it’s leveraged and secured according to the data policies of the company. The data is now decoupled from your data management control plan and no longer has a reference to its structure, purpose, data governance, and, of course, its data security.&nbsp;</p>



<p>You run a high risk that someone will leverage your data in ways that you and/or your enterprise would not approve. There could be unintended accidents such as a leak of data that should be private or purposeful misuse such as selling the data to an investor who wants to leverage the data for insider trading. &nbsp;</p>



<p>But what if your data could take all its attributes and policies along on this journey? Attributes could include valid use cases, security, and governance, and a log that tells exactly how the data is leveraged as it&#8217;s leveraged. In other words, the data would have the ability to protect and manage itself. You would be assured that the data will be used in approved ways and never fall outside of those approved parameters. Would that be of value to you?</p>



<p><strong>See also: </strong><a href="https://www.rtinsights.com/cloud-adoption-trends-of-2021-amplify-in-2022/" target="_blank" rel="noreferrer noopener">Cloud Adoption Trends of 2021 Amplify in 2022</a></p>



<h3 class="wp-block-heading">Same data, new capabilities</h3>



<p>If you Google “autonomous data,&#8221; you’ll end up with many different definitions. It&#8217;s a topic that’s been part of many Ph.D. dissertations over the years. It’s also a regular topic of conversation in the halls of database vendors, large and small. However, the autonomous data that’s coming soon will be a bit different from the structured and unstructured data of the present and past.&nbsp;</p>



<p>Here are three common attributes that will set autonomous data apart:</p>



<p><strong><em>1. The ability to self-manage when decoupled from a database.</em></strong> Autonomous data is surrounded by small, decoupled data management layers that can live on many different platforms and manage the data by using a distributed model. The autonomous data can still maintain a connection back to a database control plane, but that control plane can work across many different clouds, applications, users and even exist inside other databases.</p>



<p><strong><em>2. Support for structured and unstructured data using the same mechanisms. </em></strong>Since the control plane applies structured at the time of use, to either unstructured data or structured data that you would like to leverage differently, you can leverage this technology for both structured and unstructured data without having to reconfigure. You can manage the use of unstructured data such as PDF documents, video files, audio files, and even old text files with the same data management control plane by applying a structure to determine suggested use. You could also allow secured, monitored, and managed access no matter where the unstructured (or structured) data physically exists.&nbsp;</p>



<p><strong><em>3. The ability to provide autonomous data security, no matter where the data physically exists or if there is access to a control plane. </em></strong>Worried that your data will become vulnerable when it’s not within your direct control, or when it’s no longer communicating with a data management control plane, or if you don’t even know where the data is physically stored? That won’t be a concern. Data security stays with the data and is not part of some centralized database and database security that can only secure its centrally stored data. Moreover, the data security is truly autonomous, with the ability to defend the data no matter where it exists, using behaviors and policies that the owner of the data predefines.&nbsp;</p>



<p><strong>See also: </strong><a href="https://www.clouddatainsights.com/cloud-migration-enabling-innovation/" target="_blank" rel="noreferrer noopener">Cloud Migration: Enabling Innovation</a></p>



<h3 class="wp-block-heading">The road to autonomous data &nbsp;</h3>



<p>This autonomous data technology won’t appear as a new product or new cloud services but as a series of changes to the ways that database management systems deal with data. The focus in the past was on control of the data, including what the data is, means, does, and who has access to it. With data automation, where the data resides is no longer a factor. Indeed, the data could be scattered over 100 different cloud and non-cloud servers, even mobile systems and IoT, with all locations caring for different parts of the holistic data.</p>



<p>This distributed data paradigm is not new. We&#8217;ve been talking about it since the 70s. This older iteration just divides up the data, either single or multiple copies, for several decentralized databases connected via some network. What is new is that we now define the distribution of data not by the distribution of databases but just the data itself. No centralization is required.&nbsp;</p>



<p>A use case such as edge computing could have 1000 different chunks of data running on 1000 different devices, but each chunk does not require its own tiny database. Data automation just provides a platform for the autonomous data to exist. Autonomous data will carry out all the data management, data governance, and data security operations, no matter if the data is connected to a data management control plan or not. It also won&#8217;t matter if it’s just a single record or massive amounts of data, structured or unstructured.&nbsp;</p>



<p>The race to the autonomous data model will be gradual. We already know that the move to multicloud and other complex distributed architectures drives many enterprises into a complexity wall. The tipping point of data complexity is in sight, where data will become useless due to the restrictions of data centralization.&nbsp;</p>
<div class="saboxplugin-wrap" itemtype="http://schema.org/Person" itemscope itemprop="author"><div class="saboxplugin-tab"><div class="saboxplugin-gravatar"><img loading="lazy" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/05/David-Linthicum-1.jpg" width="100"  height="100" alt="" itemprop="image"></div><div class="saboxplugin-authorname"><a href="https://www.clouddatainsights.com/author/david-linthicum/" class="vcard author" rel="author"><span class="fn">David Linthicum</span></a></div><div class="saboxplugin-desc"><div itemprop="description"><p>David Linthicum was recently named the #1 cloud influencer in a report by Apollo Research and is typically listed as a top 10 cloud influencer, podcaster, blogger, book author, and thought leader. He started his cloud journey back in 1999 when he envisioned leveraging computing services over the open internet. David has been a CTO five times for both public and private companies, and a CEO two times in his 35-year career. He is credited with creating $4 billion dollars in shareholder return in those roles, including his current role as Chief Cloud Strategy Officer at Deloitte Consulting as a leader in the Cloud Practice.</p>
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