BUSINESS INTELLIGENCE,BIG DATA MANAGEMENT
VAST Data | September 30, 2022
VAST Data, the data platform company for the AI-powered world, today announced a strategic partnership with Dremio, the easy and open data lakehouse platform, to enable enterprises to get from data to insights faster with a hybrid, multi-cloud architecture for scalable analytics. Regardless of physical location – on-premises or in the public cloud – Dremio customers can now analyze their data anywhere by leveraging VAST’s massively parallel architecture for concurrent and near real-time data access at any scale.
VAST and Dremio are at the forefront of a market shift away from siloed data warehouses and legacy data platforms such as Hadoop. As businesses struggle with the exponential growth of data volumes and data sources, they need a highly-scalable solution for storing that data, and providing broad and concurrent access for a wide range of technical and non-technical data consumers. Paired with Dremio, VAST's Universal Storage enables organizations to escape the restrictive, walled garden environment of Hadoop and the Hadoop File System. It provides customers with an open data lakehouse platform that powers the data management, data governance, and enterprise analytics capabilities typically found in a data warehouse, powered by an all-flash data store that is purpose-built to manage large volumes of structured, semi-structured, and unstructured data.
In the spirit of public cloud object storage offerings like Amazon Simple Storage Service (S3), VAST unifies an organization’s data for analytics on a common, single-tiered and linearly scalable data platform - while also enabling customers to step into an all-flash S3 experience without the flash expense that’s common with conventional systems. Dremio provides an open data lakehouse platform that executes lightning-fast SQL queries using a common semantic layer across data sources, and a simple user interface. As a result, organizations can build capabilities that are superior to even public cloud offerings with cloud-native infrastructure that provide choice and flexibility on how and where data is managed.
“Partnering with VAST ensures Dremio users are equipped with the lakehouse data capacity and scalable high performance necessary to run their business intelligence workloads and data analytics applications. “As data volumes continue to grow, VAST’s disaggregated architecture enables users to easily scale the performance and capacity that businesses demand, and that our open data lakehouse platform delivers.”
Roger Frey, vice president of alliances at Dremio
Faster time to data access
Dremio’s open lakehouse platform enables organizations to query data directly in the data lake – and on S3 architecture – without having to copy or move data. By querying data in place, Dremio eliminates the need for complex and brittle ETL pipelines and data copies. Dremio reduces the time required to fulfill data access requests from weeks or months to just hours, and makes data teams more productive. Dremio also centralizes security and governance, and its no-copy architecture reduces network and storage costs.
Dremio’s simplified data architecture complements VAST’s all-flash Universal Storage storage platform, which reduces latency and delivers a high-performance infrastructure for analytics at any scale. VAST’s breakthrough Universal Storage data platform reduces the amount of storage capacity necessary in cloud-native environments without compromising performance, optimizing spend and space. Together, Dremio and VAST accelerate access to data for analytics, and deliver insights to a wide range of data consumers.
“We continue to see high market demand to underpin organizations’ modern data analytics infrastructure with VAST. Partnering with ecosystem leaders like Dremio drives a new approach to data analytics,” said Jeff Denworth, chief marketing officer and co-founder of VAST. “Partnering with Dremio ensures that our mutual customers have an optimized and simple out-of-the-box experience as they embrace a cloud-native architecture for their rapidly evolving data management needs.”
About VAST Data
VAST Data delivers the data platform at the heart of the AI-powered world, accelerating time-to-insight for workload-intensive applications. The performance, scalability, ease of use and cost efficiencies of VAST’s software helps enterprise organizations overcome the historic barriers to building all-flash data centers. Launched in 2019, VAST is the fastest-selling data infrastructure startup in history.
Read More
BIG DATA MANAGEMENT,DATA VISUALIZATION
AtScale | September 29, 2022
AtScale, the leading provider of semantic layer solutions for modern business intelligence and data science teams, today announced at the Semantic Layer Summit an expanded set of product capabilities for organizations working to accelerate the deployment and adoption of enterprise artificial intelligence (AI). These new capabilities leverage AtScale’s unique position within the data stack with support for common cloud data warehouse and lakehouse platforms including Google BigQuery, Microsoft Azure Synapse, Amazon Redshift, Snowflake, and Databricks.
Organizations across every industry are racing to realize the true potential of their data science and enterprise AI investments. IDC predicts spending on AI/ML solutions will grow 19.6% with over $500B spent in 2023. Despite this investment, Gartner reports that only 54% of AI models built will make it into production, with organizations struggling to generate business outcomes that justify investment to operationalize models. This disconnect creates an enormous opportunity for solutions that can simplify and accelerate the path to business impact for AI/ML initiatives.
The AtScale Enterprise semantic layer platform now incorporates two new capabilities available to all customers leveraging AtScale AI-Link:
Semantic Predictions - Predictions generated by deployed AI/ML models can be written back to cloud data platforms through AtScale. These model-generated predictive statistics inherit semantic model intelligence, including dimensional consistency and discoverability. Predictions are immediately available for exploration by business users using common BI tools (AtScale supports connectivity to Looker, PowerBI, Tableau, and Excel) and can be incorporated into augmented analytics resources for a wider range of business users. Semantic predictions accelerate the business outcomes of AI investments by making it easier and more timely to work with, share, and use AI-generated predictions.
Managed Features - AtScale creates a hub of centrally governed metrics and dimensional hierarchies that can be used to create a set of managed features for AI/ML models. Managed features can be sourced from the existing library of models maintained by data stewards or by individual work groups. Furthermore, new features created by AutoML or AI platforms can also become managed features. AtScale managed features inherit semantic context, making them more discoverable and easier to work with, consistently, at any stage in ML model development. Managed features can now be served directly from AtScale, or through a feature store like FEAST, to train models in AutoML or other AI platforms.
“Despite rising investments, greater adoption of AI/ML within the modern enterprise is still hindered by complexity. “The need for AI is huge, exploration is on the rise, but many businesses are still not able to use the predictive insights AI models can generate. Here at AtScale we can leverage our unique position in the data stack to streamline and simplify how the business can consume and use AI immediately, generating faster time to value from their enterprise AI investments.”
Gaurav Rao, Executive Vice President and General Manager of AI/ML at AtScale
About AtScale
AtScale enables smarter decision-making by accelerating the flow of data-driven insights. The company’s semantic layer platform simplifies, accelerates, and extends business intelligence and data science capabilities for enterprise customers across all industries. With AtScale, customers are empowered to democratize data, implement self-service BI and build a more agile analytics infrastructure for better, more impactful decision making.
Read More
BUSINESS INTELLIGENCE,BIG DATA MANAGEMENT,DATA ARCHITECTURE
Mode Analytics | September 30, 2022
Mode Analytics today announced that it has been recognized as a Business Intelligence Leader in the inaugural Modern Marketing Data Stack Report: Your Technology Guide to Unifying, Analyzing, and Activating the Data that Powers Amazing Customer Experiences, executed and launched by Snowflake, the Data Cloud company.
Snowflake’s data-backed report identifies the best of breed solutions used by Snowflake customers to show how marketers can leverage the Snowflake Data Cloud with accompanying partner solutions to best identify, serve, and convert valuable prospects into loyal customers. By analyzing usage patterns from a pool of nearly 6,000 customers, Snowflake identified six technology categories that organizations consider when building their marketing data stacks. These categories include:
Analytics
Integration & Modeling
Identity & Enrichment
Activation & Measurement
Business Intelligence
Data Science & Machine Learning
Focusing on companies that are active members of the Snowflake Partner Network (or ones with a comparable agreement in place with Snowflake), as well as Snowflake Marketplace Providers, the report explores each of these categories that comprise the Modern Marketing Data Stack, highlighting technology partners and their solutions as “leaders” or “ones to watch” within each category. The report also details how current Snowflake customers leverage a number of these partner technologies to enable data-driven marketing strategies and informed business decisions. Snowflake’s report provides a concrete overview of the partner solution providers and data providers marketers choose to create their data stacks.
“Marketing professionals continue to expand their investment in analytics to improve their organization’s digital marketing activities. “Mode has emerged as a leader in the Modern Marketing Data Stack, with joint customers leveraging their technology to interpret insights that lead to informed business decisions.”
Denise Persson, Chief Marketing Officer at Snowflake
Mode was identified in Snowflake’s report as a Leader in the Business Intelligence category for its particular success with Visual Explorer, Mode’s flexible visualization system that helps analysts explore data faster and provides easy-to-interpret insights to business stakeholders. Additionally, Mode and Snowflake have partnered in the past couple of years tocreate a modern data analytics stack, mobilizing the world’s data with the Snowflake Data Cloud to help joint customers quickly execute queries and perform analysis.
“Mode combines the best elements of business analytics and data science into a single platform, unlocking new ways for marketers to accelerate data-driven outcomes,” said Gaurav Rewari, CEO, Mode Analytics. “Our partnership with Snowflake makes it possible for marketing and other departments across an organization to truly centralize and interact directly with their data. With Snowflake’s single, integrated data platform, built to fully leverage the speed and flexibility of the cloud, organizations can mobilize their data in near-real time.”
About Mode Analytics
Mode’s advanced analytics platform is designed by data experts for data experts. It allows data scientists and analysts to visualize, analyze, and share data using a powerful end-to-end workflow that covers everything from early data exploration stages to presentation-ready shareable products. Unlike traditional business intelligence tools that produce static dashboards and reports, Mode brings the best of BI and data science together in a single platform, empowering everyone at your organization to use data to make high quality, high velocity decisions. Mode also supports the analytics community with free learning resources such as SQL School, open source SQL queries, and free tools for anyone analyzing public data.
Read More