Readers' Choice Awards 2019
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Trends and Applications
The ability to quickly act on information to solve problems or create value has long been the goal of many businesses. But with the combination of greater volume, variety, and velocity, the situation is becoming more vexing. Fortunately, there are business intelligence solutions today with capabilities to support strong data strategies.
To leverage the immense power of their data, organizations need a solid strategy that incorporates everything from security to data governance to the right big data technologies. Enabling both on-prem and cloud deployments—or a hybrid strategy—big data platforms today support data warehouses, data lakes, data science, engineering, machine learning, myriad database management systems, and much more.
Speed to insight matters more today than ever before. But dealing with the increasing volume of data, and the speed at which this data changes, can be a hindrance to data integration, timely analytics, and rapid decision making. Change data capture supports real-time analytics with less overhead to advance a range of initiatives such as data warehousing, real-time dashboards, data quality, and more.
DBAs and their organizations are moving to the cloud. A recent survey conducted by Unisphere Research, a division of Information Today, Inc., in partnership with Amazon Web Services, found that, on average, 25% of organizations' critical enterprise data is now managed in public clouds. The survey also found that for 60% of data managers the use of public cloud-based data resources and platforms has increased over the past year.
Cloud is now mainstream, a critical part of data environments,and this trend is only increasing. Gartner estimates that $206 billion will spent on public cloud services in 2019, up 17% from 2018, while IDC estimates that nearly half of IT spending was cloud-based in 2018, "reaching 60% of all IT infrastructure and 60%-70% of all software, services and technology spending by 2020."
One in four enterprises now regards real-time data as critical to their ongoing operations—and another one in four is actively preparing to introduce real-time data capabilities into their infrastructures. Data-driven innovation is being embraced by almost every department in the enterprise, led by outward-facing departments, with line-of-business owners and marketing departments demanding the most innovation from data.
The pressure is on. Today, organizations are under tremendous pressure from business partners, consumers, and regulators to exercise care about how they handle sensitive data of all kinds. Data governance is becoming more challenging due to a confluence of factors, including data volumes exploding, data being collected from more disparate sources, and data no longer being stored centrally, but instead in a combination of on-premise, cloud, and hybrid scenarios.
In the era of big data, volume, variety, and velocity are often mentioned as critical issues. However, at Data Summit 2019, data integration was identified as one of the most critical and disruptive problems facing organizations today.
Best Data Modeling Solution
Best Data Quality Solution
Best Data Replication Solution
Increasingly stringent data privacy regulations along with a generally lower tolerance for data mishandling, are making companies even more concerned about improving their data security postures and thwarting cyber risk.
According to an IDC report, the Global Datasphere will grow from 33 Zettabytes (ZB) in 2018 to 175ZB by 2025. "To keep up with the storage demands stemming from all this data creation, IDC forecasts that over 22ZB of storage capacity must ship across all media types from 2018 to 2025."
Best Data Virtualization Solution
Data visualization tools have evolved beyond the standard charts and graphs used in Excel spreadsheets, displaying data in more sophisticated ways such as infographics, dials and gauges, geographic maps, sparklines, heat maps, and detailed bar, pie and fever charts. The images may include interactive capabilities, enabling users to manipulate them or drill into the data for querying and analysis.
With long downtimes simply unacceptable today, organizations seek solutions with capabilities such as the ability to manage backups seamlessly, manage and monitor backups, ensure data integrity, scale efficiently, restore quickly to any point in time, and provide security features to stay in compliance with local geographic and industry mandates.
Best Database Development Solution
Social media, the Internet of Things, demands for mobile access, and real-time insights are just some of the factors that have increased the pressure on organizations to change how data is managed. And as a result there have never been so many data management choices to deal with it all.
Best Database Performance Solution
After more than 15 years, there is still probably no technology more aligned with advent of big data than Hadoop. The Apache Hadoop framework allows for the distributed processing of large datasets across compute clusters, enabling scale up from single commodity servers to thousands of machines for local computing and storage. Designed to detect and handle failures at the application layer, the framework supports high availability.
In-memory databases and technologies enable decision makers to get to the information they are seeking rapidly and more readily. While in-memory technology has been on the market for many years, today, the demand for intelligent, interactive experiences requires back-end systems and applications operating at high performance, and incorporating movement and delivery of data faster than ever before.
The Internet of things (IoT) is the inter-networking of physical devices, vehicles (also referred to as "connected devices" and "smart devices"), buildings, and other items embedded with electronics, software, sensors, actuators, and network connectivity which enable these objects to collect and exchange data.
Look to NoSQL for fast, highly scalable access to free-form data. This comes with a few costs, like consistency of reads and other safeguards common to SQL databases. But for many applications, those safeguards may well be worth trading for what NoSQL offers.
A relational database is a set of formally described tables from which data can be accessed or reassembled in many different ways without having to reorganize the database tables. The standard user and application programming interface (API) of a relational database is the Structured Query Language (SQL). SQL statements are used both for interactive queries for information from a relational database and for gathering data for reports.