The analytics capabilities of many enterprises simply aren’t keeping up with growing data volumes or the needs of the business. Perhaps it’s the inability to get the reports needed in a timely fashion, or the inability to drill down into the data in a meaningful way to identify insights. If so, you’re not alone in finding it hard to get the business insights you need out of your analytics tools.
Let’s take a closer look at some of the specific challenges facing organizations trying to get the most from their analytics tools:
- Lack of high availability. If you can’t access the data you need when you need it, it’s not helping you. Large-scale data warehouses or data lakes may not be designed for high availability, or have windows of time when they’re not accessible, leaving business analytics off-line or incomplete.
- Inability to easily access all data. Fast-moving business questions and analysis can’t always wait for perfectly formatted data. Traditional data warehouses are often too slow to run ad-hoc queries against raw fact data and organizations are forced to build data cubes or other curated data sources that lengthen the analytical process. Data lakes, once positioned as an easy, cheap solution for data storage have instead become part of the analytics problem for many organizations, since it turns out they’re better at collecting data than processing it.
- Poor scalability. Few organizations can predict exactly what type of scalability needs they will have in the future. Data analytics solutions that worked well when data sources or timeframes were limited may fail when scaled up to meet the needs of more users or the analysis of bigger sets of data.
- Inability to run mixed real-time workloads. Most organizations are now accumulating vast waves of real-time data from multiple sources. Yet existing data warehouse solutions cannot capture real-time data efficiently or in a timely manner. Too often they require data to be bulk-loaded or micro-batched, eliminating the opportunity to analyze real-time event or device data or do timely analysis on mixed workloads that involve concurrent queries on continually changing data or complicated mixes of reads, updates, loads, and queries.
- Difficulty handling high numbers of concurrent users. Business analytics is no longer something that just a few select people in the organization do. In fact, most companies have hundreds or thousands of employees that can benefit from accessing and analyzing corporate data. Yet too many organizations have data warehouses or business analytics systems that fail to keep up.
A New Approach to Getting the Most from Business Analytics
Whether you’re struggling with reports or month-end close processes that take forever to run or you are tired of waiting for real-time data to be loaded into your data warehouse, getting the most of your business analytics may be easier than you think.
The Yellowbrick data warehouse is an ideal hybrid cloud solution that provides unmatched performance for business analytics needs. Built from the ground up to be easy to manage and to provide unmatched performance with petabytes of data, Yellowbrick can support thousands of concurrent users performing complex ad hoc queries and running sophisticated reports. Its unique hybrid cloud architecture enables organizations to easily manage large, difficult-to-migrate datasets where they reside—on premises or in the cloud.
Consider these key business benefits of Yellowbrick:
- Unmatched price/performance. Unlike public cloud data warehouses that may have hidden costs, 1-3 year commitments, additional licensing costs for tools and more, Yellowbrick offers a simplified subscription-based pricing model with deterministic, predictable pricing. The Yellowbrick Data Warehouse is offered as a subscription service on any cloud or on-premises in your data center.
- Robust and efficient hybrid cloud capabilities. Hybrid-cloud solutions save organizations money, since they can protect and extend existing investments in analytics tools and infrastructure. Yellowbrick can operate seamlessly with a myriad of existing public or private clouds and other on-premises tools more effectively and efficiently than other products.
- Out-of-the-box-performance. Yellowbrick is data-ready out of the box. There’s no need to set a lot of parameters or make a lot of fine-tuned adjustments with a Yellowbrick solution. Instead it features a “load and go” design that enables it to be production-ready on the same day that it’s deployed. It’s also able to scale up to petabytes of capacity with near-linear performance and not much additional oversight. At the same time, the solution is optimized for challenging analytic environments, enabling customers to run ad hoc queries, large batch queries, business reports, ETL processes, and ODBC inserts all at the same time.
- Minimal “care and feeding.” Yellowbrick greatly reduces the amount of operational overhead required to deploy and manage. In addition, customers can easily add performance and capacity by adding compute nodes on the fly, without any downtime. Ad-hoc workloads on Yellowbrick run faster than heavily tuned, indexed queries on other databases.
- Low latency. Yellowbrick provides an extremely low-latency connection to data, resulting in much faster performance.
- Common language. The Yellowbrick data warehouse service uses standard PostgreSQL. It supports all of the rich SQL constructs you expect, including multi-thousand-line queries or running against large fact tables where the questions asked are not always known in advance.
- Common connectors. Yellowbrick has standard, common, open connectors for all applications and analytics tools. Not only is it data-model agnostic, but Yellowbrick has off-the-shelf connectors such as ODBC, JDBC, and ADO.NET to integrate seamlessly with existing applications and analytics tools. That means nothing to customize and no expensive back-end integration. Standard BI, reporting, data mining, and ETL tools all run against the system seamlessly.
- Rapid and seamless data migration. One of the key problems facing many organizations is moving data into and out of data warehouses, data marts, or data lakes in a fast and efficient manner. Yellowbrick is ideal for heavy analyses that require large amounts of data or fast loads of data sets or data marts. With Yellowbrick, if a line of business wants to analyze certain data sets or data marts they can do it quickly with Yellowbrick. It also provides seamless, real-time data intake of many types of source data, including flat ASCII, compressed data, Hadoop, S3, and more.
Yellowbrick’s hybrid cloud solution helps businesses build real-time performance into their existing on-premesis or public cloud systems. It can serve as a performance engine or data aggregator for a data lake, unlocking the business value of data locked in existing data stores. Yellowbrick’s out-of-the-box performance, minimal operational overhead requirements, low latency, common SQL language, standard connectors, and rapid data migration enables it to better address the new era of big, real-time data analytics better than any other data warehouse solution.