Lake Video Download
Jaimee Jaffy
Discover a Washington Original! Only in Lake Chelan will you find four seasons of wine, over 300 days of sunshine, stunning natural beauty and adventures that you can tune to your own tastes. 50.5 miles of crystal clear, glacier-fed lake, surrounded by vineyards, mountains and small-town charm promise an array of activities as unique as the people who come here to play or make Lake Chelan their forever home.
Mono Lake is an ancient saline lake located at the eastern edge of the Sierra Nevada in California. Home to trillions of brine shrimp, millions of birds, and world-famous tufa towers, its tributary streams also supply water to Los Angeles, nearly 350 miles to the south. After a successful legal fight stopped excessive diversions, ongoing advocacy has shown that balanced solutions mean enough water for both people and the environment.
Lake Guntersville State Park rests along the banks of the Tennessee River in Northeast Alabama. Whether you are looking for a resort-style retreat or an outdoor adventure in the 6,000 acres of natural woodlands, Lake Guntersville State Park will satisfy all your needs. Among the many recreational offerings are an 18-hole championship golf course, the Screaming Eagle Zipline, a beach complex, an outdoor nature center, excellent fishing in Alabama's largest lake, 36 miles of hiking and biking trails, weekly guided hikes, and a day-use area.
There is always something exciting happening at our historic property! Click below to learn more about special events, the exclusive lakefront Harbor Club residential community and stay up to date on the major room renovations occurring this winter season at the Main Lodge.
Organizations that successfully generate business value from their data, will outperform their peers. An Aberdeen survey saw organizations who implemented a data lake outperforming similar companies by 9% in organic revenue growth. These leaders were able to do new types of analytics like machine learning over new sources like log files, data from click-streams, social media, and internet connected devices stored in the data lake. This helped them to identify, and act upon opportunities for business growth faster by attracting and retaining customers, boosting productivity, proactively maintaining devices, and making informed decisions.
Data lakes allow you to import any amount of data that can come in real-time. Data is collected from multiple sources, and moved into the data lake in its original format. This process allows you to scale to data of any size, while saving time of defining data structures, schema, and transformations.
Data lakes allow you to store relational data like operational databases and data from line of business applications, and non-relational data like mobile apps, IoT devices, and social media. They also give you the ability to understand what data is in the lake through crawling, cataloging, and indexing of data. Finally, data must be secured to ensure your data assets are protected.
Data lakes allow various roles in your organization like data scientists, data developers, and business analysts to access data with their choice of analytic tools and frameworks. This includes open source frameworks such as Apache Hadoop, Presto, and Apache Spark, and commercial offerings from data warehouse and business intelligence vendors. Data lakes allow you to run analytics without the need to move your data to a separate analytics system.
Data lakes will allow organizations to generate different types of insights including reporting on historical data, and doing machine learning where models are built to forecast likely outcomes, and suggest a range of prescribed actions to achieve the optimal result.
A data lake is different, because it stores relational data from line of business applications, and non-relational data from mobile apps, IoT devices, and social media. The structure of the data or schema is not defined when data is captured. This means you can store all of your data without careful design or the need to know what questions you might need answers for in the future. Different types of analytics on your data like SQL queries, big data analytics, full text search, real-time analytics, and machine learning can be used to uncover insights.
The ability to harness more data, from more sources, in less time, and empowering users to collaborate and analyze data in different ways leads to better, faster decision making. Examples where Data lakes have added value include:
A Data lake can combine customer data from a CRM platform with social media analytics, a marketing platform that includes buying history, and incident tickets to empower the business to understand the most profitable customer cohort, the cause of customer churn, and the promotions or rewards that will increase loyalty.
The Internet of Things (IoT) introduces more ways to collect data on processes like manufacturing, with real-time data coming from internet connected devices. A data lake makes it easy to store, and run analytics on machine-generated IoT data to discover ways to reduce operational costs, and increase quality.
The main challenge with a data lake architecture is that raw data is stored with no oversight of the contents. For a data lake to make data usable, it needs to have defined mechanisms to catalog, and secure data. Without these elements, data cannot be found, or trusted resulting in a data swamp." Meeting the needs of wider audiences require data lakes to have governance, semantic consistency, and access controls.
Data lakes are an ideal workload to be deployed in the cloud, because the cloud provides performance, scalability, reliability, availability, a diverse set of analytic engines, and massive economies of scale. ESG research found 39% of respondents considering cloud as their primary deployment for analytics, 41% for data warehouses, and 43% for Spark. The top reasons customers perceived the cloud as an advantage for Data lakes are better security, faster time to deployment, better availability, more frequent feature/functionality updates, more elasticity, more geographic coverage, and costs linked to actual utilization.
AWS provides the most secure, scalable, comprehensive, and cost-effective portfolio of services that enable customers to build their data lake in the cloud, analyze all their data, including data from IoT devices with a variety of analytical approaches including machine learning. As a result, there are more organizations running their data lakes and analytics on AWS than anywhere else with customers like NETFLIX, Zillow, NASDAQ, Yelp, iRobot, and FINRA trusting AWS to run their business critical analytics workloads.
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