Osano, a data compliance platform, raises $11M

Osano

Osano, a data privacy platform that helps websites become compliant with international regulations, today announced that it closed a $11 million funding round led by Jump Capital, bringing its total raised to $22.3 million. The company says that the money will be used to support international expansion as well as hire additional sales, marketing, and engineering staff.

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Database startup SingleStore raises $80M

SingleStore

Database startup SingleStore today announced that it raised $80 million in a series F funding tranche led by Insight Partners, bringing its total raised to over $319 million at a post-money valuation “just shy” of $1 billion. Khosla Ventures, Dell Capital, Rev IV, Glynn Capital, and Google Ventures also participated in the round, which CEO Raj Verma says will be put toward product development and improving awareness of SingleStore’s managed database service offering.

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Involve.ai boosts AI-driven customer data platform with $16M

Involve AI

Involve.ai, a startup using AI to bolster customer success, today announced it has raised $16 million in a series A round led by Sapphire Ventures and other investors. The company says the capital will be put toward product development and hiring on the engineering, data science, and go-to-market sides.

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The business value of clustering algorithms

A single type of machine learning algorithm can be used to identify fake news, filter spam, and personalize marketing materials. Known as clustering algorithms, or “clustering” for short, they can automatically discover natural groupings of events, people, and objects in large datasets.

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Data observability startup Monte Carlo raises $60M

Monte Carlo

Monte Carlo, a data observability startup based in San Francisco, California, today announced that it raised $60 million in funding from Iconiq Growth with participation from Salesforce Ventures, Accel, GGV Capital, and Redpoint Ventures. It brings the company’s total raised to date to $101 million, and CEO Barr Moses says it’ll be put toward bringing partners onboard, growing the company’s workforce, and expanding to new markets including Asia-Pacific, Europe, the Middle East, and Africa.

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Customer engagement analytics startup Retain.ai nabs $23M

Retain AI

Retain.ai, a platform that gives enterprises a view of customer engagement across teams, processes, and apps, has raised $23 million in a funding round led by Emergence Capital, with participation from Baseline Ventures, Upside Partnership, and Afore Capital. The new funding will be used to support growth and more than double Retain.ai’s workforce by the end of 2021, cofounder and CEO Eric Chernoff said. This round brings the company’s total raised to more than $27 million to date.

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FullStory nabs $103M for customer experience analytics

Fullstory

FullStory, a customer experience analytics company, today announced it has closed a $103 million series D round led by Permira, Kleiner Perkins, GV, Salesforce Ventures, and others. The startup says the new capital, which brings its valuation to $1.8 billion and total funding to $170 million, will be used to expand its business internationally and enhance its digital experience observability platform.

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How to democratize access to Data Insights for businesses of all sizes

Data access

Messy government data has been part of the reason we’ve been unable to understand the COVID-19 pandemic. If federal organizations can’t decode big data, what hope do small businesses have?We’ve never had this much data on our hands. But as the material we’re dealing with grows, we need to ensure the skeleton that supports it is evolving sturdily alongside it.That’s no small feat, given the breakneck speed at which our data load increases every day. The more data we have at our fingertips, the more unbridled its potential is – but the harder it also becomes to harness it, especially for companies with less of a tech background or smaller R&D capabilities. A lack of accessible and affordable tooling would leave smaller players behind, making access to big data analytics an increasingly exclusive privilege.Nevertheless, the past decade has shown us that data analytics and tools have the capacity to speedily advance to accommodate the growing wave of information.And Development Analytics has a big role to play in that. As all companies are also becoming tech companies, engineering teams need to develop software that captures big data and uses machine learning so they can stay in the game. Development Analytics tools like Waydev are there to help engineering managers fully understand and improve the development process of these analytics projects. So it’s a bit of an analytics inception if you will.In today’s landscape, three essential pillars have emerged in data analytics – visualization, open source, and AI. Here’s how the future of data analytics and tools can make this sphere more democratic, and what this means for software development.Data visualization tools will make big data digestibleStartups are no stranger to big data. They can get huge swaths of it relatively straightforward, but that doesn’t mean they hold the keys to understanding it.One of the first data visualization tools, the Gantt chart, was invented in 1910 to visually track data across large teams. Big data is typically unstructured, making it difficult to draw conclusions from the figures. But if companies can’t accurately interpret data, its value is wasted. Raw data doesn’t always tell a story; to do that it has to be processed and curated in a more visually appealing form.The next generation of big data tools will prioritize simple data visualization for all users. Graphics, maps, tables, and patterns are far more intuitive than text and can stitch seemingly abstract stats together – which is especially useful for small business leaders who don’t have a tech background. In fact, we’re already seeing the shift with tools like Visme and Tableau, which transform big data into engaging charts and infographics. Visualization becomes all the more powerful when coupled with relevant data sources to provide business insights and help leaders gain a better understanding of their team’s work.Gantt charts may have been an innovation for its time but in the Agile software development environment, they are of no use.Development Analytics tools like Waydev and Pluralsight Flow use user-friendly dashboards, heatmaps, color-coding, charts, and diagrams to signal progress, issues, and steer the user’s attention to the important values.Open source will improve data tools’ transparency and qualityThe popularization of data tools has paved the way for open source software like Android (the operating system used by Google phones), which can be freely used or modified by anyone. Whereas data tools used to be exclusively reserved for paying customers (read: deep-pocketed corporations), open source tooling is free and made for the public, by the public.Many tools that were once closed source have made the switch to open source in recent years. For example, Apache Hadoop, the framework that uses programming models for distributed processing of large data sets, quickly became supported by NoSQL databases and other open source infrastructure when it started to be widely adopted. Today, the majority of infrastructure used to store and stream large volumes of data is open source, including databases like MongoDB and tools like TensorFlow. Even the notoriously secretive Apple has hopped on the bandwagon, releasing its programming language, Swift, as open source in 2014. Data science wouldn’t be as large in scope, nor as efficient, without open source tooling. As data grows, small businesses need more sophisticated data processing tools, which will benefit from open contributions. The more people that contribute to code, the higher the quality of the tool. And, as more people own a cell phone, are active online, and share information digitally, data sets will continue to grow exponentially and push demand for data-processing tools. In order to maximize the functionality and interoperability of these tools, businesses should start embracing open source from the get-go. AI data tools will become mainstream (at last)Despite finding its roots in the 1950s, AI didn’t really get started until the 1990s. In 1997, the world chess champion was beaten by IBM’s AI chess-playing program, Deep Blue. In the same year, Dragon System developed and implemented its speech-recognition software on Windows. The two creations were a big step for AI, and for many people, signaled its impending uptake across industries. The reality though, is that AI is yet to be adopted on a mass scale. A 2020 survey revealed that only 8.9% of US businesses use AI, and the ones that do are mostly big companies that have the money to invest in the tech: not surprising when companies pay between $6,000 and $300,000 for AI software.Although the uptake is relatively slow, early signs of more financially flexible AI exist, and they go a long way toward democratizing data tools for all companies, regardless of their size. TakeawayData and analytics tools won’t be fizzling out any time soon. Both have progressed considerably in recent years, and with expanding data sets at the heart of these tools, they’ll not only get better, they’ll also get smarter.In software development, in particular, we’ll be seeing widespread adoption of development analytics in the following years. Engineering leaders will keep investing in Development Analytics tools so they can meet the growing demands of their organizations, and remain ahead of the innovation curve. This only means we’re getting one step closer to normalizing a data-driven culture in software engineering.Related StoriesTagsJoin Hacker Noon Create your free account to unlock your custom reading experience.

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How Data Analytics gonna be the Decision Maker in the Future?

Laptop analytics dashboard

Data analytics is the most popular term in many industries. It can change the situation of the company with concentration. Many companies are integrating the data analytical services with their work to develop and improve their routine works. By applying a suitable approach to the required work will help a lot to take the decision and help to maintain the work constantly progressive. This blog will help you to know the importance of data analytics needs in the future.

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Trilogy of Data, analytics, AI is accelerating innovation across industries [with Video]

Tom Davenport & Tom Siebel

Technology industry veterans Tom Davenport and Tom Seibel have seen firsthand how data, analytics and artificial intelligence have changed business models over the past three decades. In a conversation with ThoughtSpot Chief Data Strategy Officer Cindi Howson at VentureBeat’s Transform 2021 conference on Tuesday, Davenport and Siebel shared their insights into how technology has boosted innovation and how it can transform industries, as well as the dangers it presents.

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The problems with Big Data and how AI can help, an interview with Andrew Gryaznov, CTO at HyperC

Columns of light

What is wrong with Big Data, how can classical AI solve these problems, and why is it possible now? I had the opportunity to sit down and talk about these issues in greater detail with Andrew Gryaznov, CTO at HyperC and the expert in AI for business efficiency.

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Opaque raises $9.5M for encrypted data analytics

Opaque

Opaque, a startup that helps organizations analyze encrypted data in the cloud, today announced that it closed a $9.5 million seed funding round led by Intel Capital with contributions from Race Capital, The House Fund, and FactoryHQ. Cofounder Raluca Ada Popa says that the funds will help to expand Opaque’s ongoing contributions to the open source and data security communities.

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Database optimization startup Silk raises $55M

Silk AI

Silk, a platform designed to improve database performance, today announced it has raised $55 million in a series B funding round led by S Capital. The company says that the funds will be used to support its sales and marketing operations and expand its engineering team as the demand for cloud environments rises in the wake of the pandemic.

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Dataminr acquires event tracker WatchKeeper to augment real-time alerts

Dataminr acquires Watchkeeper

Dataminr, a New York-based company specializing in real-time information alerts, today announced that it purchased WatchKeeper, a data geovisualization platform, for an undisclosed amount. Dataminr, which says that the acquisition — its first — was a direct result of its series F funding, characterizes the move as one of its first to fuel the growth of its private sector business.

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Augtera Networks raises $13M to apply AI to networking

Augtera

Augtera Networks, a company leveraging AI to allow networks to keep up with increasing scale, today announced that it raised $13 million in series A funding led by Intel Capital. The financing brings Augtera’s total raised to $18 million to date, and CEO Rahul Aggarwal says that it’ll drive the next phase of Augtera’s product development around auto-remediation and deeper integrations with cloud ecosystems including Amazon Web Services and Microsoft Azure.

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Visier raises $125M to power HR analytics with data

Viser

Cloud-based analytics platform Visier, which focuses on human resources (HR) and workforce strategy applications, today announced that it closed a $125 million series E round led by Goldman Sachs at a post-money valuation of over $1 billion. With the investment, Visier joins a small list of HR technology providers that have raised more than $100 million in a single funding tranche.

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Incorta nabs $120M to power business data analytics

Incorta

Incorta, an analytics platform designed to speed up data ingestion, this week announced it has raised $120 million in funding contributed by Prysm Capital, with participation from National Grid Ventures, GV, Kleiner Perkins, M12, Sorenson Capital, Telstra Ventures, Ron Wohl, and Silicon Valley Bank (in the form of a credit facility). CEO Scott Jones says the capital, which brings Incorta’s total raised to $195 million, will be used to expand go-to-market operations and meet demand for Incorta’s analytics products.

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Crate.io raises $10M to grow its database platform

Crate IO

Crate.io, a startup developing a database platform called CrateDB, today announced that it raised $10 million in additional funding (including $2 million in debt) from Draper Esprit, Vito Ventures, and individual investors. CEO Eva Schönleitner says that the proceeds, which bring the company’s total raised to $31 million, will be put toward expanding Crate.io’s sales teams, the CrateDB ecosystem’s functionality and partner integrations, and the open source developer community around CrateDB.

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