Artificial intelligence (AI) and large language models (LLMs) have come a long way since their inception in the 1950s. From the pioneering research of English mathematician and logician Alan Turing to the recent breakthroughs achieved by models like GPT-3/GPT-4, AI has undeniably transformed industries and revolutionized human-computer interactions.
At TCS, we help companies shift their enterprise data warehouse (EDW) platforms to the cloud as well as offering IT services. We’re extremely familiar with just how tricky a cloud migration can be, especially when it involves moving historical business data.
Amazon S3 is a standout storage service known for its ease of use, power, and affordability. When combined with Apache Kafka, a popular streaming platform, it can significantly reduce costs and enhance service levels. In this post, we’ll explore various ways S3 is put to work in streaming data platforms.
Tracking and analyzing your BigQuery costs will make you feel more at ease when running queries.
Follow this Fivetran formula to centralize scattered customer data and build a Customer 360.
In the dynamic world of machine learning operations (MLOps), staying ahead of the curve is essential. That’s why we’re excited to announce the Cloudera Model Registry as generally available, a game-changer that’s set to transform the way you manage your machine learning models in production environments.
The growing field of precision medicine holds incredible promise for delivering better patient care and medical innovation, but there are barriers to greater implementation. As an emerging approach for disease treatment and prevention, precision medicine takes into account individual variability in genes, environment and lifestyle for each person. Its implementation has primarily been hastened by reducing sequencing costs.
Explore how you can create a GraphQL API using BigQuery and open-source software Hasura.
With its rise in popularity generative AI has emerged as a top CEO priority, and the importance of performant, seamless, and secure data management and analytics solutions to power those AI applications is essential. Cloudera Private Cloud Data Services is a comprehensive platform that empowers organizations to deliver trusted enterprise data at scale in order to deliver fast, actionable insights and trusted AI.
In a previous blog post (How To Survive an Apache Kafka® Outage) I outlined the effects on applications during partial or total Kafka cluster outages and proposed some architectural strategies to handle these types of service interruptions. The applications most heavily impacted by this type of outage are external interfaces that receive data, do not control request flow, and possibly perform some form of business transaction with the outside world before producing to Kafka.
The past year has seen an unprecedented AI hype wave triggered by the launch of OpenAI’s ChatGPT. Analysis abounds on whether the hype is real, where value will accrue and whether generative AI-first product builders have a real shot at category disruption or creation. As frenzied R&D and market activity continue unabated, market maps and take after take continue to drop hot. But what about revenue?
ERP systems run the world’s businesses. These stalwart systems are great at managing records and processes for finance, operations, supply chain management and more. But their insights need an upgrade. That’s the case put forward by Maxa, an enterprise-grade startup that has made it their mission to reinvent the way companies access and use ERP data for transformational insights.
Follow this formula to streamline financial statements and automate data for accurate financial analysis.
Stepping into the world of Apache Kafka® can feel a bit daunting at first. I know this firsthand—while I have a background in real-time messaging systems, shifting into Kafka’s terminology and concepts seemed dense and complex. There’s a wealth of information out there, and it’s sometimes difficult to find the best (and, ideally, free) resources.
2024 is going to be an important transition year for artificial intelligence. 2023 was the public debut of generative AI and large language models (LLMs), a year of amazement, excitement, occasional panic and, yes, more than a little bit of hype. The year ahead is when businesses begin to make the promise of advanced artificial intelligence real, and we’ll begin seeing the effects on how we work and live.
In one of our recent blog posts, about six key predictions for Enterprise AI in 2024, we noted that while businesses will know which use cases they want to test, they likely won’t know which ones will deliver ROI against their AI and ML investments. That’s problematic, because in our first survey this year, we found that 57% of respondents’ boards expect a double-digit increase in revenue from AI/ML investments in the coming fiscal year, while 37% expect a single-digit increase.
The greater tech community was front row for a high-stakes corporate saga this past weekend, complete with more plot twists than the Succession series finale.
Event tracking is a critical component of product analytics, providing deep insights into how users interact with your product. It involves monitoring and analyzing specific actions (events) taken by users within your application or website. These insights are pivotal for enhancing user experience, improving product features, and driving growth.
CityFibre is one of the U.K’.s biggest fibre networks, connecting millions to high-speed broadband. Piyush Shandilya, Data Architect at CityFibre explains how the company uses Snowflake to process and analyze large, integrated data sets at speed, powering future growth and delivering next-gen connectivity. CityFibre is the U.K.’s third largest gigabit network and is predicted to connect 8 million people by 2025.
Fivetran, LTIMindtree and Snowflake unveil DecisionsCX, empowering enterprises with Customer 360 for hyper-personalization.
The enterprise app market has been growing faster than ever before, due to the recent spike in demand for AI / ML workloads. These new types of apps operate over large sets of data, have increasingly higher compute demands, require strict data privacy protections, provide very sophisticated web experiences, and need to be secure at all stages of their life cycles. While such apps are being created at a very fast pace, there are two main challenges.
Explore the architectural concepts that power BigQuery’s support for semi-structured JSON, which eliminates the need for complex preprocessing and provides schema flexibility, intuitive querying and the scalability benefits, at large scale.
BigQuery cross-region dataset replication allows you to replicate any dataset across regions, for additional geo-redundancy.
Large Language Models (LLMs) have now evolved to include capabilities that simplify and/or augment a wide range of jobs. As enterprises consider wide-scale adoption of LLMs for use cases across their workforce or within applications, it’s important to note that while foundation models provide logic and the ability to understand commands, they lack the core knowledge of the business. That’s where fine-tuning becomes a critical step.
The telecom industry is undergoing a monumental transformation. The rise of new technologies such as 5G, cloud computing, and the Internet of Things (IoT) is putting pressure on telecom operators to find new ways to improve the performance of their networks, reduce costs and provide better customer service. Cost pressures especially are incentivizing telecoms to find new ways to implement automation and more efficient processes to help optimize operations and employee productivity.
If you’re building an application today, one of your top product priorities for 2024 is almost certainly adding an AI copilot to your application. AI copilots – AI assistants powered by large language models (LLMs) and deeply embedded into applications – offer one of the most compelling opportunities to reimagine applications since the dawn of the internet.
Data is key to building resilience and achieving operational excellence—but first, your data must be intelligible. Luckily, modern BI solutions have intuitive interfaces that allow business users to build interactive data visualizations and contextual data stories. With this knowledge at their fingertips, your entire organization is empowered to make data-driven decisions.
For customers using Microsoft’s Data Lake offerings, they can securely land data in Delta Lake format from any one of Fivetran’s 400+ source connectors.
Of the many things one might take for granted, access to banking and financial services may not immediately come to mind. But as a thought experiment, imagine trying to buy a home or a car without the ability to take out a loan. Try depending on cash payments from your employer, or relying on alternative banking solutions like short-term payday loans, check-cashing services, and prepaid debit cards.
Organizations are transforming their industries through the power of data analytics and AI. A recent McKinsey survey finds that 75% expect generative AI (GenAI) to “cause significant or disruptive change in the nature of their industry’s competition in the next three years.” AI enables businesses to launch innovative new products, gain insights into their business, and boost profitability through technologies that help them outperform competitors.
See why Snowflake’s healthcare customers rate the Data Cloud high in performance and cost savings. Each year, KLAS Research interviews thousands of healthcare professionals about the IT solutions and services their organizations use. Since 1996, the analyst firm has been leading the healthcare IT (HIT) industry in providing accurate, honest and impartial insights about vendor solutions and customer satisfaction metrics.
Have you heard this quote from Edwards Deming? – “In God we trust, all others bring data.” In today’s competitive landscape, if you’re not measuring your performance and closely analyzing each relevant data point, you’re not going to see much success with your strategies. This is the golden rule no matter what type of business you run – whether you’re a small, local jewelry store or Coca-Cola. And KPIs (key performance indicators) help us do just that.
Recent Fivetran data model releases help companies get insights out-of-the-box and seamlessly build a Customer 360.
The ability to perform custom text analysis in a variety of ways makes our toolset even more comprehensive and user-friendly.
In the dynamic world of product development and management, the role of a Product Analyst has become increasingly pivotal. These professionals are at the forefront of deciphering market trends, customer behaviors, and product performance through data analysis. Their insights play a crucial role in shaping product strategies, ensuring that products not only meet current market demands but also anticipate future trends.
Have you ever wondered how massive business and consumer apps handle that kind of scale with concurrent users? To deploy high-performance applications at scale, a rugged operational database is essential. Cloudera Operational Database (COD) is a high-performance and highly scalable operational database designed for powering the biggest data applications on the planet at any scale.
Be transparent with employees about the benefits of data in talent processes.
At this year’s Current, we introduced the public preview of our serverless Apache Flink® service, making it easier than ever to take advantage of stream processing without the complexities of infrastructure management. This first iteration of the service offers the Flink SQL API, which adheres to the ANSI standard and enables any user familiar with SQL to use Flink.
With 38% of data teams spending between 20% and 40% of their time fixing data pipelines¹, delivering reliable data to end users can be an expensive activity for data teams. With Kensu’s latest integration with Azure Data Factory, ADF users now benefit from the ability to observe data within their Azure Data Factory pipelines and receive valuable insights into data lineage, schema changes, and data quality metrics.
Databricks, Google Cloud and dbt Labs recognize Fivetran as their 2023 Partner of the Year.
SYDNEY, NSW — 08 November 2023. Logilica, a leader for Software Engineering Intelligence (SEI), today announced their support for open interfaces to their engineering analytics data warehouse and platform. Logilica enables enterprises now to bring their own software lifecycle data and upload them through Logilica’s published APIs, opening up their flagship platform to a wide variety of tools and solutions.
From connected cars and fleets of commercial vehicles to connected smart home devices, it’s estimated there are more than 14 billion products equipped with sensors, processors, software and connectivity worldwide—a number that is projected to almost double by 2030.
Ensuring a seamless data experience that complies with regulatory frameworks, particularly in the public sector, is crucial. Research from the U.K. government found as many as 32% of businesses and 24% of charities suffered online breaches or cyberattacks in the last 12 months. In this increasingly interconnected world, national stability depends on thoughtful data governance and safeguarding.
Are you struggling to manage the ever-increasing volume and variety of data in today’s constantly evolving landscape of modern data architectures? The vast tapestry of data types spanning structured, semi-structured, and unstructured data means data professionals need to be proficient with various data formats such as ORC, Parquet, Avro, CSV, and Apache Iceberg tables, to cover the ever growing spectrum of datasets – be they images, videos, sensor data, or other type of media content.
As we head into 2024, AI continues to evolve at breakneck speed. The adoption of AI in large organizations is no longer a matter of “if,” but “how fast.” Companies have realized that harnessing the power of AI is not only a competitive advantage but also a necessity for staying relevant in today’s dynamic market. In this blog post, we’ll look at AI within the enterprise and outline six key predictions for the coming year.
To say the global retail market is challenging today would be a gross understatement. A rising cost of living, demanding consumer expectations, supply chain disruption and unforeseen public health crises like COVID-19 all contribute to the erosion of retailers’ bottom lines. However, retail media has in recent years emerged as an increasingly promising guard against these economic uncertainties and can even serve as a profitable revenue stream.
OpenAI DevDay 2023 is upon us. We're excited by what some of the announcements mean for Continual and will be revealing more about Continual soon. In the meantime, you can watch the livestream and replay here: There's never been a better time to build an AI copilot for your application.
In an era defined by rapid technological advancements and increasing consumer expectations, the automotive industry faces unprecedented challenges and opportunities. Vehicle manufacturers must constantly innovate to remain competitive, and one indispensable tool in their arsenal is product analytics. This article explores compelling reasons why product analytics is essential for the automotive sector and suggests some additional considerations. So let's dive in!
When running automated tests frequently on your website, at one point it may be essential to keep your website statistics consistent with correct visitor counts, conversions, and geo-location data. The impact of such skewed data from automation can lead to pricy mistakes for incorrect ad targeting and the business economy statistics, hence it can be important to exclude test automation from analytics data.
Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse, data lake and data lakehouse, and distributed patterns such as data mesh. Each of these architectures has its own unique strengths and tradeoffs.
Snowflake’s single, cross-cloud governance model has always been a powerful differentiator, enabling customers to manage their increasingly complex data ecosystems with simplicity and ease. As a result, Snowflake is enhancing its governance capabilities that thousands of customers already rely on through Snowflake Horizon. Snowflake Horizon is Snowflake’s built-in governance solution with a unified set of compliance, security, privacy, interoperability, and access capabilities.
In the ever-evolving world of data management, Snowflake is at the forefront of empowering our customers to make informed decisions about data while ensuring cost efficiency and control. Admins know that managing and optimizing platform costs can be a complex and time-consuming task. To help them more intuitively understand, control and optimize spend from one centralized place, Snowflake is introducing the new Cost Management Interface (private preview).
Generative AI (GenAI) and large language models (LLMs) are disrupting the way we work at a global scale. Snowflake is excited to announce an innovative product lineup that brings our platform’s ease of use, security and governance to the GenAI world.
Snowflake is announcing new product capabilities that are changing how developers build, deliver, distribute and operate their applications.
Snowflake has invested heavily in extending the Data Cloud to AI/ML workloads, starting in 2021 with the introduction of Snowpark, the set of libraries and runtimes in Snowflake that securely deploy and process Python and other popular programming languages.
Generative AI is unlocking new ways to drive innovation, improve productivity and derive more value from data. For organizations to fully capitalize on this potential, it’s critical that everyone — not just those with AI expertise — is able to access and use generative AI.
Third-party vendors can now leverage Fivetran software development kits to build their own Fivetran connectors and destinations.
At Cloudera, we continuously strive to empower organizations to unlock the full potential of their data, catalyzing innovation and driving actionable insights. And so we are thrilled to introduce our latest applied ML prototype (AMP)—a large language model (LLM) chatbot customized with website data using Meta’s Llama2 LLM and Pinecone’s vector database.