Data With a Chance of Cloud: Exploring What Cloud Offers for Data Management
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“Cloud-powered companies are much more likely to have an enterprise-wide data strategy than other companies (88% versus 59%). This means they develop a streamlined architecture to modernize their data into an integrated view, create governance structures, and concentrate on building the skills and operational changes needed to become a data-driven organization.” Source: PWC’s 2023 Cloud Business Survey |
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Real-Life Examples A biotechnology firm utilized cloud computing to quickly provide the initial clinical supply of a COVID-19 vaccine contender for Phase I trials within a mere 42 days. This achievement was made possible, in part, by revolutionary advancements that employed expandable cloud-based data storage and processing. These innovations played a role in expediting procedures that guarantee the safety and effectiveness of the vaccine. Financial institutions use cloud solutions for various elements of customer service management. They automate calls by employing voice recognition algorithms and cognitive agents (AI-driven virtual assistants) that guide customers to relevant information or connect them to a human agent as needed. In the realm of fraud and debt analysis, cloud-based solutions amplify the predictive capabilities of conventional early-warning systems. Car manufacturers are also embracing cloud technology. One company employs a shared cloud platform that caters to 124 manufacturing facilities, 500 storage locations, and 1,500 suppliers. This platform consolidates up-to-the-minute data from machines and systems to monitor supply chain activities and provide valuable insights into shop floor operations. The adoption of cloud technology has the potential to reduce factory expenses by 30 percent by the year 2025, while simultaneously igniting advancements and creative solutions. Source: McKinsey |
1) Cloud Storage
Managing data storage can be challenging, particularly in today’s world. With an enormous amount of data to collect and analyze, it can be a complicated process that takes a lot of time to produce meaningful insights. Fortunately, cloud solutions offer a variety of advantages for data storage compared to traditional on-prem IT solutions. Cloud systems enable organizations to increase or decrease their data storage capacity depending on their data volume, providing easy and cost-effective scalability options. The cloud also allows data to be stored on multiple servers worldwide. If any data center faces a problem (a fire, natural disaster, etc.), data is already backed up and can be recovered from a server elsewhere. This multi-cloud availability is essential for operations to run smoothly during a crisis. Multi-cloud availability also reduces latency since it automatically selects the best geographical location to store data, enabling faster user access. Cloud systems typically provide storage tiers optimized for different use cases like frequent access, infrequent access, and archival storage, which makes it possible for companies to select the most suitable storage tier option depending on their data access patterns.2) Database as a Service (DBaaS)
Data management can be incredibly costly, mainly if your company relies on traditional on-prem solutions for storing, analyzing, and managing data. Costs associated with infrastructure, maintenance, software, and IT personnel can increase significantly for organizations, particularly in industries characterized by high transaction traffic and the collection of large amounts of user data. Database as a Service (DBaaS) allows enterprises to waive all these costs by switching to the cloud, enabling them to reduce organizational costs. It is also much faster to deploy compared to on-prem IT solutions. Companies can seamlessly migrate to the cloud and enjoy their data management tools right away.
3) Data Lakes & Warehouses
Data Lakes are centralized archives that companies utilize to store colossal amounts of data, whether it is unstructured or structured. As the name explains, data lakes are used for collecting data effectively in one place and possess numerous advantages for data management efforts. Data Lakes allow companies to save all types of data, including but not limited to social media, user behavior, logs, messages, videos, images, and geolocation. Data Lakes reduce the burden of data analysts by gathering data in the same location, allowing seamless access and a wide range of analysis tools. It is also relatively cost-efficient since companies are only paying what they use, making it possible to reduce operational costs and allocate their funds efficiently. Data Lakes also have multiple tools for refining unstructured/raw data fit for use, enhancing data transformation. Data Warehouses, on the other hand, share some similarities with data lakes in principle, but the primary purpose of a data warehouse is focused on analysis and reporting. A data warehouse can store and optimize historical data for use with business intelligence tools. It enhances reporting by analyzing vast amounts of data very quickly, reducing latency and allowing organizations to manage highly complex data sets with greater ease.|
“The new challenges that cloud computing brings with it call for an intelligent data centre architecture where the network is a platform for transparency, management and security.” – Viktor Hagen, Data Centre Architect, Cisco Systems GmbH |
4) Content Delivery Networks (CDN)
A Content Delivery Network (CDN) is a server network spread out to different locations around the world that primarily distributes all sorts of online content like texts, videos, images, and audio. CDNs can replicate content and store it in different servers in multiple locations. Depending on the user’s location, CDNs can send the desired content from the nearest server available. This helps reduce latency when transferring data and remarkably enhances speed, efficiency, cost optimization, and user experience. Faster loading screens equal better service, satisfied customers, lower costs, and increased efficiency for companies, which are the foundations for competitive advantage.
5) Data Integration & ETL
Today, data is vastly scattered among different organizations and service providers, making it very challenging to gather and analyze data sets. Traditional on-prem solutions are no longer sufficient in addressing these challenges and are gradually becoming obsolete. This has led companies to switch to cloud solutions, which provide effortless real-time data integration and ETL (extract, transform, load) processes, resulting in better access and control over data. Companies can extract data from various sources, use third-party tools for deeper analysis, better interpret results, and gain all-encompassing insights in real-time. With the cloud’s enhanced communication tools, analysts and managers can seamlessly collaborate and brainstorm, enabling them to make informed and strategic business decisions.6) AI & ML Tools
Technological advancements have been shaping the way we humans analyze and interpret data, but soon, humans won’t be the ones conducting comprehensive analyses. The revolution has already started: AI and ML are transforming data management and governance processes as we know them. AI can quickly analyze large data sets in real-time, enabling companies to save time and resources. Data analysts can focus on other aspects of the business, with the cloud doing all the heavy lifting to create comprehensive analyses. With ML, Gen AI can spot repetitive data patterns, leading to a deeper understanding of consumer behavior and more accurate predictions for organizations. AI can also detect inconsistencies in the data, allowing companies to improve the accuracy of their data-driven decisions while lowering the risk of errors and fraud.
7) Data Governance & Security
Gathering, storing, and analyzing data is one thing; preventing it from going under the wrong hands is another. Data breaches are getting more frequent than ever with increasing cyber attacks, putting companies in a pickle where a single breach can determine their entire faith. Companies accustomed to on-prem solutions have doubts about migrating to the cloud since they have given up on controlling their data. Although this concern is understandable, it is not entirely accurate. In fact, cloud systems provide much better data governance and security solutions than traditional methods, making them a suitable choice for organizations of all sizes and sectors. Data encryption feature in cloud systems allows companies to safely store and transfer data, providing robust security against data breaches. The cloud also offers advanced control regarding data access, enabling companies to authorize who can access what data set seamlessly. Additionally, managers can track who has accessed certain types of data and what actions they’ve taken, allowing for improved audits. The cloud also offers easy data recovery and backup, so if a data breach occurs, companies can get back on track as soon as possible, regaining their company data that is essential for operations.⭐⭐⭐
Kartaca has a proven track record of successfully implementing diverse big-data solutions across various industries. Our dedication to tailoring solutions to individual client needs, prioritizing data security and compliance, and delivering tangible, scalable results showcases our expertise. We help you get the maximum benefit from your data through profiling, integration with ETL, real-time analysis, segmentation, and action-based data generation. We achieved “Data Analytics” Specialization from Google Cloud, proving that we have established Google Cloud services practice, consistent customer success, and proven technical capabilities in this field. If you are looking for a trusted and reliable partner to help harness the power of data-driven insights, please visit this page for more information and contact us.Kartaca is a Premier Partner for Google Cloud in the Sell and Service Engagement Models with “Cloud Migration” and “Data Analytics” specializations.
TL;DR
What are some advantages of using cloud storage for data management?
Cloud storage offers benefits such as scalability, multi-cloud availability, reduced latency, and optimized storage tiers.
How does Database as a Service (DBaaS) reduce costs for organizations?
DBaaS helps organizations reduce costs by eliminating expenses related to infrastructure, maintenance, software, and IT personnel.
What is the primary purpose of a Data Warehouse?
A Data Warehouse is primarily focused on analysis and reporting, optimizing historical data for use with business intelligence tools.
How do Content Delivery Networks (CDNs) enhance user experience?
CDNs reduce latency by replicating and distributing content to servers in multiple locations, resulting in faster loading times and improved user experience.
How can AI and ML tools benefit data management?
AI and ML tools can quickly analyze data, spot patterns, and detect inconsistencies, leading to more accurate insights and predictions while saving time and resources.
Author: Cem Cetinguc
Published on: Nov 27,2023
