The top 5 enterprise analytics stories of 2021 (and a peek into 2022)

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In 2021, there has been an analytical transformation this year, from database to baseball, no-code AI for data scientists, graph analytics and even events.

Going forward in 2022, Gartner’s head of research, Chris Howard, and his team wrote in a report on his Leadership Vision for Data and Top 3 Strategic Priorities for Analytics Leaders for 2022 that “progressive data and analytical leaders are moving communication away from tools and technologies. This evolution will take time, but the data and analytics leaders are in the best position to help orchestrate this change. “

Furthermore, Gartner’s report predicts that adaptive governance will become more prevalent in 2022: “Traditional one-size-fits-all approaches to data and analytics governance cannot deliver the value, scale, and speed that digital business demands. Adaptive governance data and analytics enable leaders to flexibly select different governance styles for different business scenarios. “

The enterprise analytics sector has forecast a lot coming this year. Here’s a look at some of the region’s top stories from 2021, and where these themes can take the industry to the next level.

Databases capture real-time analytics capabilities and integration

Rockset has integrated its analytics database with relational databases of both MySQL and PostgreSQL to enable organizations to run queries against structured data in real time.

Instead of migrating data to a cloud data warehouse to run analytics, organizations can now offload analytics processing into a Rockset database running on a single platform.

The company’s approach is designed to analyze structured relational data as well as semi-structured, geographic and time-series data in real time. Critical analytical queries can also be measured to connect to other databases, data lakes or event streams. In addition to integration with open source relational databases, the company also provides connectors between Mongodibi, Dynamodibi, Kafka, Kinesis, Amazon Web Services and Google Cloud Platform, among others.

What has come out most about this enhancement, however, is not specific to Rockset. “As the world moves from batch to real-time analytics,” the company said in its press release, “and from analysts running manual queries to applications running programmatic queries, traditional data warehouses are dwindling.” This trend of real-time analytics is driven by the rapid move by many companies in virtual and all-online infrastructure due to the epidemic. Real-time analytics in virtual space will allow companies to index, strategize and create new applications more accurately using their data.

The popular baseball analytics platform moves to the cloud

For baseball fans, it is well known that the data provided by MLB goes beyond the traditional hits, runs and errors – a game that is increasingly complex in its data and statistics as it is on its ever-growing list. Time limits and league rules.

Fans now regularly visit online sites that use this data to analyze almost every aspect of baseball: the chances of top pitching, the players who hit the most at a particular ballpark during a particular time of day, and so on.

One of those sites is FanGraphs, which transitioned to the SQL Relational Database Platform, which relies on processing and analyzing structured data in a curated example of an open source MariadB database, deployed on the Google Cloud Platform.

Fenographs uses the data it collects to enable its editorial teams to distribute articles and podcasts that project, for example, playoff odds for the team based on the results of SQL queries generated by the company. This insight can help a baseball fan participating in a fictional league, someone who wants to place a more informed bet on the game instead of legalizing gambling, or to update the game developer. MLB The Show Video game. All of the above requires a high volume of data.

One of the things that attracts FanGraphs to MariadB is the level of performance it can achieve using the Database-A-Service (DBaaS) platform.

“On top [Maria DB’s] The simplicity and operation of SkySQL, the exceptional service of our SkyDBAs has enabled us to fully offload our database responsibilities. That help goes far beyond daily maintenance, backup and disaster recovery. We feel that our SkyDB monitors things that we need to monitor in order to secure and optimize our operations, “said David Appelman, founder and CEO of Fenographs, in a press release.

The explosion of data has called for an explosion of efficiency to manage it, and that is a trend that the industry can expect to headline more in 2022.

Data scientists will soon get their hands on no-code analytics

SparkBeyond, a company that helps analysts generate new answers to business problems without the need for any code using AI, has released SparkBeyond Discovery.

The company aims to automate the job of a data scientist. Typically, a data scientist looking for a solution to a problem can generate and test 10 or more hypotheses a day. With SparkBeyond’s machine, millions of hypotheses per minute can be generated from the data it takes advantage of from the open web and client’s internal data, the company says. In addition, SparkBeyond explains its findings in natural language so that no-code analysts can understand it.

The company says the auto-generation of the model predicted for its analysts puts it in a unique position in the AI ​​services marketplace. The purpose of most AI tools is to assist the data scientist in the modeling and testing process while the data scientist already comes up with hypotheses for testing.

The significance here inevitably comes down to “time is money.” For example, the more time a data scientist can save in solving problems and testing hypotheses, the more money the company saves in return. “Analytics and data science teams can now take advantage of AI to uncover insights hidden in complex data and build predictive models without the need for coding. [while leveraging the] An AI-powered platform for making quick business decisions, “SparkBeyon said in an October press release.

A service with the ability to explore such a large number of hypotheses per minute based on internal and external data sources to reveal previously unknown drivers of business and visual results, and explain its findings in natural language to individuals who may not even need to code. , Is quite a success in the analytics space.

Well known companies using SparkBeyond Discovery include McKinsey, Baker McKenzie, Hitachi, PepsiCo, Santander and others.

Life is becoming increasingly divided between the virtual and the individual – the analysis must follow

Hubilo, a platform that helps businesses of all sizes host virtual and hybrid events and gain access to real-time data and analytics, raised શ્રેણી 23.5 million in its Category A funding round earlier this year.

Investments in companies like Hubilo that integrate tools for virtual and personal functions, events, meetings and activities will probably continue until 2022 as the world enters the second year of the global epidemic. Digital conferences, meetups and events can be scaled more easily and with less resources than their brick-and-mortar counterparts, and shifting to hybrid and virtual platforms generates significant amounts of data in individual events that would not otherwise be possible. Proves valuable for companies to track and correlate business objectives.

Hubilo promises to increase data and scalability to its customers. Using Hubilo’s platform, event organizers can access the connection data on visitors, including the number of logins and new users versus active users. In addition, event sponsors can also determine which visitors are likely to purchase from them based on their affiliation with the virtual booth. The data includes the number of business cards received, profile views, file downloads and more.

The platform can also track visitor activities, such as attending booths or participating in video demonstrations, and then recommending similar activities. From a business perspective, sponsors or sales staff can use these features to access potential leads through a feature called Hubilo “Potential Leads.”

Its integration capabilities are now key even for companies operating in hybrid or fully remote capabilities. Hubilo has a common “one-click approach to go-to-market platforms, including HubSpot, Salesforce and Marketo, enabling companies to show ROI through event data integrated with their existing workflow,” its press release said. Integrating analytics tools with CRM and sales platforms is an important trend that will continue to evolve because the world is not about getting things back in person, but, If They should do so, and instead what they can get from hybrid approaches and tools.

The graph database gets improved

What do Panama Papers researchers, NASA engineers, and Fortune 500 leaders have in common? It all depends heavily on graphs and databases.

Neo4j, a graph database company that claims to popularize the term graph database and aims to be a leader in the graph database industry, has signaled through its growth this year that graph technology is becoming a cornerstone of the stack.

Across industry sectors, Graph Database offers a variety of usage cases that are both operational and analytical. One of the major advantages they have over other databases is their ability to instinctively generate models and quickly generate data models and queries for highly interconnected domains. In an increasingly interconnected world, this is proving to be valuable for companies.

What was then the early adopter of the game has become snowball in the mainstream, and it is still growing. Here’s how Gartner put it when he included the graph in his Top 10 Data and Analytics Technology Trends for 2021.

The interest of tech and data decision makers continues to grow as Graph Data Master plays a role in managing data, tracking laundered money, connecting Facebook friends and empowering search page rankers in influential search engines.

With the reported increase in the amount of data that companies are now increasingly storing and processing in the digital world, tools that provide flexibility for the interpretation, modeling and use of data will become key and their use is sure to continue.

According to Neo4j, it is definitely capable of providing its users. ,Graph databases store nodes and relationships instead of tables or documents. Data is stored in the same way you can sketch ideas on a whiteboard. Your data is stored without being limited to a predefined model, allowing a very flexible way to think about and use it, “the press release reads.

So what’s next for 2022? The analytics landscape will become increasingly complex in its capabilities, while at the same time becoming more user-friendly for researchers, developers, data scientists and analytics professionals.

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