Big Data Management
Syntasa | October 09, 2023
Syntasa, a leading provider of composable martech solutions, has unveiled a new feature designed to empower companies interested in Customer Data Platforms (CDPs). This new capability allows companies to leverage the 'Data Ready for CDPs' solution within a private cloud environment, allowing organizations to effortlessly import relevant customer data for utilization within their chosen CDP.
As businesses expand their horizons towards gaining a comprehensive understanding of customer journeys and experiences across various channels, the adoption of CDPs has surged to enhance marketing and customer engagement endeavors. With privacy regulations becoming increasingly stringent, companies are turning to zero and first-party data to fuel their CDP program. However, the process of collecting, cleaning, and transforming this zero and first-party data from internal systems to effectively power CDPs has proven to be a formidable challenge for marketing teams.
On the journey to implementing CDPs, marketing teams have encountered a significant obstacle in the form of extended deployment timelines. Conventional CDP programs often demand 6-12 months merely to launch the Minimum Viable Product (MVP). This protracted timeline poses a substantial hurdle for businesses eager to reap the benefits of a CDP swiftly. Furthermore, manual data preparation for CDPs persists as a labor-intensive and error-prone procedure, resulting in increased time and costs for integrating each new data point with a CDP. Compounding the issue, customer data is typically fragmented across diverse systems, often lacking cleanliness and necessitating robust collaboration among various teams to render it actionable. This complexity makes integrating data from disparate sources into a CDP a daunting task.
Syntasa's core platform operates within the customer's own Virtual Private Cloud (VPC), affording them direct access to raw data for cleansing and transformation, facilitated by a spectrum of low-code to full-code transformations. Ultimately, the marketing team gains the autonomy to select data through a user-friendly interface and connect it to the CDP of their choice, all without necessitating technical team support.
In addition to fostering a collaborative environment where data and marketing teams work synergistically, the solution incorporates data observability components that monitor every data field transmitted to the CDP. This feature enables prompt identification of data issues, preventing them from impacting business Key Performance Indicators weeks later.
About Syntasa for Marketing
Syntasa for Marketing offers composable martech solutions featuring a range of application options from no-code to low-code and pro-code. These solutions orchestrate cloud-native services and harness the latest advancements in AI and machine learning to derive insights from digital behavior and autonomously activate these insights. The company's solutions simplify the cleansing and transforming process of onsite and offsite customer data to deliver meaningful hyper-personalization solutions fueled directly by first-party data. Additionally, the platform provides martech solutions for constructing and deploying AI/ML data science models for audience building and analysis, as well as orchestrating audience-centric omnichannel marketing campaigns across paid media, CRM, onsite personalization, and martech tools.
Dremio | September 15, 2023
Dremio, a renowned easy and open data lakehouse solution provider, has recently introduced its next-gen Reflections technology, marking a transformative milestone in SQL query acceleration. Dremio Reflections facilitate sub-second analytics performance across an organization's entire data ecosystem, irrespective of data location. This groundbreaking technology is redefining data access and analysis, ensuring that valuable insights are derived efficiently and swiftly, all while reducing costs to merely one-third of a typical cloud data warehouse.
Reflections represent Dremio's innovative SQL query acceleration technology. Queries that leverage Reflections exhibit performance gains ranging from 10 to 100 times faster than their non-accelerated counterparts. This latest release introduces the Dremio Reflection Recommender, a pioneering feature that empowers users to accelerate Business Intelligence workloads in a matter of seconds. The Reflection Recommender automatically evaluates an organization's SQL queries and generates recommended Reflections to accelerate them.
Tomer Shiran, founder of Dremio, commented,
Dremio Reflections accelerate SQL queries by orders of magnitude, eliminating the need for BI extracts/imports and enabling companies to run their most mission-critical BI workloads directly on a lakehouse. With automatic recommendations and next-generation incremental updates, we've made it even easier for organizations to take advantage of this innovative technology.
[Source: Business Wire]
Reflection Recommender eliminates the need for labor-intensive manual data and workload analysis, making the process of obtaining the fastest and most intelligent query results effortless, requiring only a few simple actions. The user-friendly nature of the Reflection Recommender puts advanced query acceleration capabilities within the reach of all users, significantly saving both time and expenses.
Dremio has also refined the process of refreshing Reflections to further bolster query performance and drive cost efficiencies. It now intelligently refreshes Reflections on Apache Iceberg tables, promptly capturing incremental data changes. This innovative approach obviates the requirement for complete data refreshes, resulting in speedier updates and reduced compute expenses.
Dremio Reflections eliminates the need for data teams to export data from the data lakehouse into BI extracts or imports for analytical reasons and overcomes performance bottlenecks for BI dashboards and reports. In addition, Reflections negate the necessity of creating precomputed tables within the data lake or data warehouse to achieve sub-second performance for BI workloads, reducing the workload and complexity for data teams.
Dremio is a leading, easy and open data lakehouse solution provider, offering organizations the versatility of self-service analytics coupled with the functionality of a data warehouse and the flexibility of a data lake. Dremio's platform empowers users to harness the lightning-fast SQL query service alongside various processing engines, all on the same dataset. The company distinguishes itself through a pioneering data-as-code methodology akin to Git, which facilitates data experimentation, version control, and governance. This innovative approach enhances agility and empowers organizations to explore and manage their data resources with unprecedented efficiency. Furthermore, Dremio offers a fully managed service that expedites organizations' entry into analytics, allowing them to commence their data-driven journey within minutes.
Business Wire | October 04, 2023
Wiiisdom, the pioneer in AnalyticsOps, today announced Wiiisdom Ops for Power BI, a new governance offering designed to deliver trusted data and analytics at scale. This SaaS-based solution, part of the AnalyticsOps portfolio from Wiiisdom, unlocks and automates new testing capabilities and integrated BI content management workflows for Microsoft Power BI.
Data and analytics governance is a critical enabler of business success, yet many people are still spending the majority of their time finding and resolving errors. Ventana Research predicts that through 2025, governance issues will remain a significant concern for more than one-half of organizations, limiting the deployment and therefore the realized value of analytics investments.
Our research shows two-thirds of organizations consider it very important to improve their data governance and only half of are governing their analytic objects, said David Menninger, SVP & Research Director, Ventana Research. Analytical operations solves this challenge by automating analytics governance, allowing all stakeholders within an organization to mitigate risks and make data-driven decisions. The AnalyticsOps portfolio of products from Wiiisdom, including the new solution, Wiiisdom Ops for Power BI, helps to ensure data is accurate, up-to-date, and consistent for trusted analyses.
Wiiisdom is on a mission to simplify and automate governance for analytics so decision-makers have quality, trusted data that they can use for decision-making. By streamlining testing, deploying, and monitoring as an integrated workflow across the entire organization, data leaders can provide timely insights that will drive value to their business, without sacrificing quality and trust.
“With more than 15 years of experience solving the toughest business intelligence challenges, we have a unique understanding of the problems that today’s data leaders face,” said Sebastien Goiffon, Wiiisdom Founder and CEO. “The launch of Wiiisdom Ops for Power BI is another step in our mission to minimize risk and increase trust in an organization’s data so business leaders across the globe can confidently make data-driven decisions.”
Wiiisdom Ops for Power BI automates dataset and report testing and streamlines analytics governance workflows, so organizations can easily validate datasets and trust that reports are accurate. The new offering allows users to:
Test and deploy content at scale: improve productivity and increase confidence with cloud-native, automated testing for all Power BI content across an organization;
Catch errors to minimize risk: build and run statistical validations, value checks, regression tests, and more to identify errors, and then document test results to comply with business and regulatory requirements; and
Build trust in data and analytics: ensure content is accurate and reliable so organizations can maximize the value of Microsoft Power BI investment and drive stakeholder adoption across the enterprise.
The introduction of Wiiisdom Ops for Power BI builds on the tremendous traction that Wiiisdom has achieved over the last 12 months. The company continues to attract top talent, adding several new go-to-market leaders from Tableau, including Michael Holcomb, VP, Customer Success and Jeremy Blaney, VP, Product Marketing, who deeply understand modern BI and customer pain points. Additionally, the company introduced a new partner program that brings together data and analytics consulting partners and world-class resellers to further scale the business.
Wiiisdom Ops for Power BI, which was unveiled at the Microsoft Power Platform Conference in Las Vegas, is available now directly and on Microsoft AppSource and Microsoft Azure Marketplace. To learn more about Wiiisdom Ops for Power BI, please check out the blog post or visit: https://wiiisdom.com/wiiisdom-ops/power-bi/
Wiiisdom is the pioneer in AnalyticsOps, building no-code, enterprise-grade solutions that simplify governance for analytics and business intelligence platforms like Tableau, Microsoft Power BI, and SAP BusinessObjects. The company offers automated BI testing capabilities and integrated workflows for content lifecycle management that make it easy to comply with governance policies at scale. For more than 15 years, Wiiisdom's solutions have helped organizations of every type, including Fortune 100 companies, build trust in data and analytics, ensuring leaders can make confident data-driven decisions. Learn more at Wiiisdom.com.
Big Data Management
Kinetica | September 22, 2023
Kinetica, a renowned speed layer for generative AI and real-time analytics, has recently unveiled a native Large Language Model (LLM) integrated with Kinetica's innovative architecture. This empowers users to perform ad-hoc data analysis on real-time, structured data with the ease of natural language, all without the need for external API calls and without data ever leaving the secure confines of the customer's environment. This significant milestone follows Kinetica's prior innovation as the first analytic database to integrate with OpenAI.
Amid the LLM fervor, enterprises and government agencies are actively seeking inventive ways to automate various business functions while safeguarding sensitive information that could be exposed through fine-tuning or prompt augmentation. Public LLMs, exemplified by OpenAI's GPT 3.5, raise valid concerns regarding privacy and security. These concerns are effectively mitigated through native offerings, seamlessly integrated into the Kinetica deployment, and securely nestled within the customer's network perimeter.
Beyond its superior security features, Kinetica's native LLM is finely tuned to the syntax and industry-specific data definitions, spanning domains such as telecommunications, automotive, financial services, logistics, and more. This tailored approach ensures the generation of more reliable and precise SQL queries. Notably, this capability extends beyond conventional SQL, enabling efficient handling of intricate tasks essential for enhanced decision-making capabilities, particularly for time-series, graph, and spatial inquiries. Kinetica's approach to fine-tuning places emphasis on optimizing SQL generation to deliver consistent and accurate results, in stark contrast to more conventional methods that prioritize creativity but yield diverse and unpredictable responses. This steadfast commitment to reliable SQL query outcomes offers businesses and users the peace of mind they deserve.
Illustrating the practical impact of this innovation, the US Air Force has been collaborating closely with Kinetica to leverage advanced analytics on sensor data, enabling swift identification and response to potential threats. This partnership contributes significantly to the safety and security of the national airspace system. The US Air Force now employs Kinetica's embedded LLM to detect airspace threats and anomalies using natural language.
Kinetica's database excels in converting natural language queries into SQL, delivering responses in mere seconds, even when faced with complex or unfamiliar questions. Furthermore, Kinetica seamlessly combines various analytics modes, including time series, spatial, graph, and machine learning, thereby expanding the range of queries it can effectively address. What truly enables Kinetica to excel in conversational query processing is its ingenious use of native vectorization. In a vectorized query engine, data is organized into fixed-size blocks called vectors, enabling parallel query operations on these vectors. This stands in contrast to traditional approaches that process individual data elements sequentially. The result is significantly accelerated query execution, all within a smaller compute footprint. This remarkable speed is made possible by the utilization of GPUs and the latest CPU advancements, which enable simultaneous calculations on multiple data elements, thereby greatly enhancing the processing speed of computation-intensive tasks across multiple cores or threads.
Kinetica is a pioneering company at the forefront of real-time analytics and is the creator of the groundbreaking real-time analytical database specially designed for sensor and machine data. The company offers native vectorized analytics capabilities in the fields of generative AI, spatial analysis, time-series modeling, and graph processing. A distinguished array of the world's largest enterprises spanning diverse sectors, including the public sector, financial services, telecommunications, energy, healthcare, retail, and automotive industries, entrusts Kinetica to forge novel solutions in the realms of time-series data and spatial analysis. The company's clientele includes various illustrious organizations such as the US Air Force, Citibank, Ford, T-Mobile, and numerous others.