January 16, 2018, RE•WORK

Algomus is a rapidly growing Detroit area startup that has built Algo the world’s first Analyst Workbot and Enterprise ML powered Big Data Analytics platform for media & entertainment companies, manufacturers, distributors, and retailers. Algomus, who is partnering with RE•WORK for the AI Assistant Summit in San Francisco this January 25 – 26 have just launched Algo 2.0, making their AI enabled workbot even smarter.

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January 11, 2018, AI Trends

“You have to think about the business problems first before you drive the tools in that direction,” said John Daly, Senior Vice President of Worldwide Production Services at Sony Pictures Entertainment.

“Daly co-developed an AI tool from Algomus, which automatically generates data reports and supports natural language queries.”

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Business Intelligence and Enterprise AI come together with a Smart Assistant

January 9, 2018, PRNewswire

LAS VEGASJan. 9, 2018 /PRNewswire/ — Algomus, Inc. headquartered in Troy, MI launches their 2nd generation Enterprise Analytics Workbot Algo 2.0 at CES 2018. Through the increased application of Machine Learning, including Deep Learning and Robotic Process Automation (RPA) Algo is taking on a more important role in the daily operations of his enterprise customers. The new UI is streamlined, conversational, and context-aware. Algo 2.0 has been optimized to produce answers to complex questions and analytical calculations with flexibility and speed. Improvements in the Natural Language Processing engine and a new Predictive Text feature make the user experience smooth and intuitive.

Key New Features

  • Context-Aware Conversational Interface
  • Chat and Search Based Interaction with Data
  • Multiple Measure Q&A Capability
  • Data Science and Analytical Workflow Automation
  • Custom Calculators, Recommenders and Simulators
  • Enhanced Forecasting Capabilities
  • A/B Test Tracking
  • Data Storyboarding via PowerPoint
  • Collaboration Features: Shared Contexts and Favorites
  • Workflow Integration via API

Algo co-creator and Algomus CEO Amjad Hussain says “Algo 2.0 is transforming from an Askbot to a Workbot, and transforming organizations from being reactive to proactive with their data. It is a big step forward for us and our customers. Algo is aimed at growing the collaborative intelligence profile of our customers, with people and AI agents working hand in hand to deliver exponential business outcomes.”

 

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There are many trends coming to the foreground of AI, machine learning, and business intelligence. This article will be talking briefly about some of these trends and why they are coming to light. A link to the in-depth report by Tableau can be found at the bottom of the page.

Do not Fear AI

Is AI the destructive force that will destroy all jobs and the world as we know it? The media and Hollywood have depicted AI as such, however this is not the case at all. At this point in time, machine learning and AI has become a daily tool in business intelligence. These tools are giving time back to their human Analyst counterparts. Analysts are using machine learning and AI software to better understand their company’s data in a more timely fashion.

Liberal Arts Impact on AI

In the upcoming months Liberal Arts will be playing a bigger role in the building of AI and machine learning software. Data scientists are realizing they not only need the data analyzed to be accurate but also tell a story that anyone can understand, including those without a technical background.

NLP (Natural Language Processing) Promise

NLP refers to the way we interact with the AI through the UI (user interface). Companies are beginning to want all level of employees to have access to the data provided by their AI software. The problem many of these companies face is that most of their employees do not have a technical background and no idea how to query a piece of data. This is where NLP comes into play; AI software can process queries in natural language instead of using specific codes. e.g. I want to know the Sales for Item “001”  by day at Store “2045”

Multi-Cloud Capabilities

The move to multi-cloud storage is becoming an ever-increasing desire within big companies. Companies don’t want to be limited to one storage method that may not provide the best performance for their data needs. Though multi-cloud architecture has many benefits, it also has its costs, one of which being the actual overhead cost of running this type of multi-cloud environment.

Rise of the CDO (Chief Data Officer)

With understanding data and analytics becoming a core competency more and more companies are creating a position of CDO. This position allows them to join the C-suite with the CEO, CTO and CIO. This new position gives the CDO the ability to attend the C-level meetings and actually affect change within the company. Due to the creation of the CDO position, companies are showing just how important it is to understand their data and manage it successfully.

Crowdsourcing Governance

Crowdsourcing governance is a fancy term for allowing customers to shape who has access to specific data within a company using self-service analytics. It gets the right information into the right hands while keeping that same information out of the wrong hands.

Data Insurance

Data is more valuable than ever. We have seen countless data breaches over the last few years and will most likely see many more. With customer data becoming so valuable we are going to see a rise in data insurance. This insurance will protect companies from being responsible for a breach of their customer data.

Data Engineering Roles

As data analysis software continues to grow in use and value we will see a rise in data engineering roles over the next several years. Data engineers will begin to transform from more architecture-centric roles to a more user-centric approach within their organizations.

Location of Things

“Location of things” is in connection to IoT (internet of things). We are seeing companies trying to capture location-based data from IoT devices. Gartner, predicts there will be 2.4 billion IoT devices online by 2020. The problem is that companies are trying to collect and compile all this location data within their internal data structures, while most of these structures are not capable of accepting that quantity of data. This is going to lead to great innovations for IoT data storage.

Academics Investments

With data analytics growing in all industries the demand for future data scientists will continue to grow. Due to this high demand for data engineers and data scientists we will begin to see more and more universities offering some sort of academic training in these categories over the next several years.

 

Read the full report by Tableau Here:

https://www.tableau.com/reports/business-intelligence-trends#ai

A huge thanks to everyone that came out to our first workshop event in Bentonville, AR! We had so much fun doing a Walmart Store 1 walk-thru (did you know there is a Dunkin Donuts inside!!), visiting customers, and holding our first Analytics Edge Workshop at the 21c Hotel.

The Workshop was incredibly well attended and we had some great dialogue with suppliers and others in the community about the potential of AI for business process automation and how easy access to Analytics can give anyone in an organization the opportunity to be strategic in their roles.

We also want to give a big thanks to John Daly of Sony Pictures Home Entertainment for joining us as a guest speaker, it is always inspiring to hear him talk about the transformation they have been able to achieve in such a short time!

We look forward to being back in Bentonville very soon!

In a 2016 research reportWhy Artificial Intelligence is the Future of Growth, Accenture found that adoption of artificial intelligence tech across all industries may double economic growth rates by 2035. AI investment is expected to increase labor productivity by 40 percent. In fact, 70 percent of executives say they plan to “significantly increase” AI investment.

In the realm of inventory and supply-chain management, AI adoption, specifically the use of optimization algorithms, is revolutionizing inventory agility – reducing stock depletions and maximizing stock levels.

“The use of AI in supply chains is helping businesses innovate rapidly by reducing the time to market and evolve by establishing an agile supply chain capable of foreseeing and dealing with uncertainties,” says Accenture Managing Director Manish Chandra. “AI armed with predictive analytics can analyze massive amounts of data generated by the supply chains and help organizations move to a more proactive form of supply chain management.”

Supply chain processes generate giga-tons of data, and AI can deploy predictive analytics to make sense of it all. Freshly updated and analyzed data then builds a solid foundation when it comes to real-time vision and information flow. Every key player across the supply chain is empowered with the best data and maximizes it accordingly.

AI is no longer an “ain’t-it-cool” innovation in the industry but rather a necessity. With the erosion of the brick-and-mortar model and rise of real-time consumer expectations, supply chain/inventory management practices must embrace machine learning that far outpaces the speed of human thought and action. Consider these stats from the 2017 MHI Industry report concerning the speed of supply-chain transactions from just one e-tailer on Black Friday:

“A reported 426 orders per second were generated from the website throughout the day. That equates to over 36 million order transactions, an estimated 250 million picking lines at the distribution centers (DC), 40 million DC package loading scans, 40 million inbound sortation hub scans, 40 million outbound sortation hub scans, 40 million inbound regional sortation facility scans and 40 million outbound delivery truck scans.”

How should industry leaders respond? The answer, according to the report, is clear. Supply-chain companies must embed “analysis, data, and reasoning into the decision-making process. Position analytics as a core capability across the entire organization, from strategic planners through line workers, providing insight at the point of action.”

As Accenture economic research director Mark Purdy concludes, companies that survive will fully invest in the potential power of AI going forward: “To fulfill the promise of AI, relevant stakeholders must be thoroughly prepared – intellectually, technologically, politically, ethically and socially – to address the benefits and challenges that can arise as artificial intelligence becomes more integrated in our daily lives.”

There are many trends coming to the foreground of AI, machine learning, and business intelligence in 2017. This article will be talking briefly about these trends and a link to the in-depth report by Tableau can be found at the bottom of the page.

BI (Business Intelligence) the New Norm

In 2017 we will see a trend of more and more companies using modern business intelligence, allowing analytics to be performed by all employees, not just data scientists and engineers.

Collaboration between Machines and Humans Strengthens

The collaboration and sharing of data is going to move from one-direction, spreadsheets and emails, to an interactive flow of data between multiple parties and their live data stream.

Data Will Become Equal

All data will be equally accessible and understandable. We will be able to access all our data without the worry of it being stored in the same format.

Anyone will be able to Data Prep.

Just as self-service analytics is becoming more accessible to non-technical employees, so will the ability to understand and prep data without the need of a technical background.

Imbedded BI is Allowing Analytics to Grow Everywhere

Business applications like Salesforce are placing analytic tools in the hands of people never before exposed to data. These tools are extending the reach of analytics in our day-to-day lives and we most likely are unaware that we are using them.

Work with Data in a Natural Way

In the next year we will see people being able to access and communicate with their data in a more natural way. We will see this more with the integration of natural language interfaces within AI networks.

Cloud Based Analytics

With data being stored in the cloud we will soon see analytics being conducted there as well. Cloud analytics will be faster and able to scale at a much quicker pace.

Data Literacy will Become a Necessity 

With Data analytics and predictive analysis moving to the mainstream we will see a need for all level of employees needing to be able to read and understand their company’s data.

 

Read the full report by Tableau Here:

https://www.tableau.com/learn/whitepapers/top-10-business-intelligence-trends-2017