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Databases are the cornerstone of many modern business applications for controlling payroll, tracking customer orders or storing and releasing any business-critical information. With the right additional business intelligence tools, companies can get all kinds of insights from their big data side, for example, creating sales trends to inform future decisions. But when it comes to making accurate predictions from historical data, that is a completely new ball game that requires a variety of skills and technologies.
This is something. Mind DB He plans to solve it by using a platform to help anyone see machine learning (ML) with big data insights. According to the company, “Enterprise Database wants to democratize machine learning by giving it a mind.”
A.D. Founded in 2017, Berkeley, California-based Mind DB allows companies to make direct predictions from their database using standard SQL commands and view them in the application or analytics platform of their choice.
MindsDB announced this week that it has raised $ 3.75 million to further expand its product and market. Total financial support About $ 7.6 million. The company has announced a partnership with well-known database brands, including Snowflake, SingleStore and DataStax, which bring the MindsDB ML platform directly to those databases.
Using the past to predict the future
There are so many usage issues for MindsDB, such as predicting customer behavior, reducing congestion, improving employee retention, finding unusual things in industry processes, giving credit-risk points and predicting product demand – using this information to find out what this might be. It looks like the last day.
For example, analysts in a large retail chain may want to know how much inventory they need to meet demand. You can ask questions and view the corner by connecting their database (for example, MySQL, MariaDB, Snowflake, or PostgreSQL) to MindsDB and then connecting MindsDB to their BI device (for example, Table Tableau or Looker).
George Torres, CEO of MindsDB, told VentureBeat, “Your database can give you a better picture of your database because that’s why databases are designed.” Detailed prediction tests can be solved with a few standard SQL commands.
According to Torres, MindsDB In-Database ML (I-DBML) allows you to create, train and use ML models in SQL, which looks like tables in a database.
“We believe that I-DBML is the best way to implement ML and we believe that all databases should have this capability, which is why we have partnered with some of the best databases in the world,” Torres said. “Provides ML to the data as much as possible, integrates ML models into virtual databases, and can be requested in simple SQL descriptions.”
MindsDB is sent in Three broad differences – Free; Open source incarnation Which can be distributed anywhere; An enterprise version that includes additional support and services; And the recently launched cloud-based hosting, which is a usage fee.
The open source community has remained a major focus for MindsDB so far, with tens of thousands of installations from developers around the world – including developers working for companies such as PayPal, Verizon, Samsung and American Express. While this organic approach will continue to be a major part of MindsDB’s growth strategy, Torres said the company is promoting its products to companies in many industries, although it does not have the freedom to name.
We are in the process of verifying a number of Fortune 100 customers with the most confidential information of business, including financial services, retail, manufacturing and gaming companies – and [this] It prohibits disclosure, ”says Torres.
The problem that MindsDB is trying to fix is that it will only affect the vertical and wide range of businesses in all types of business – even large companies do not want to upgrade their AI armor from scratch.
“If you have a strong and functional enterprise database, you have everything you need to implement machine learning from MindsDB,” Torres said. “Enterprises have invested a lot of resources DatabasesAnd some have spent decades trying to perfect their data storage. Then, over the past few years, as ML capacity began to grow, enterprises by nature wanted to use them for better forecasting and decision-making.
Although companies can They want Challenges to extract, modify, and load to make better predictions from their data (ETL) All the information that goes into other systems is complex and does not always produce good results. In MindsDB, the data remains in the main database.
“In this way, you are reducing the project schedule for years or months to hours, and you are also significantly reducing the points of fall and expense,” Torres said.
Machine Learning Switzerland
Depending on how you think about the scale of the problem, the competition is very broad. According to I.I. Tools: Many big players have emerged to arm developers and analysts. VTC-supported data center And H2OBut Torres sees these companies as partners rather than direct competitors. “We believe we have created the best way to bring intelligence directly to the database, and this is something you can use,” Torres said.
And cloud platform providers such as Amazon, Google and Microsoft are offering add-on machine learning to their customers. In those cases, however, these services are actually ways of selling more than their core products, which is computing and storage. – Torres looks forward to working with these cloud giants in the future. “We are an independent player – we are machine learning Switzerland,” Torres added.
MindDB seed funding includes investments from a number of well-known sponsors, including Open ocean, MariaDB Founder Patrick Bachman as Partner, YCombinator (MindsDB graduated YC Summer 2020 Bach), Walden Catalyst Ventures, Speed Invest and Berkeley SkyDek Fund.
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