Reddit posts will appear in Bing's search results, and its data will be piped into Power BI for marketers to track brand-related comments.

Microsoft is bringing the self-proclaimed “front page of the internet” to the pages of its search results.

Microsoft has struck a deal with Reddit to pipe data from the social network into Bing’s search results, as well as Power BI’s analytics dashboard, the companies announced on Wednesday.

Now, when people search on Bing, posts published to Reddit may be included in the search results. For example, if a person’s query asks something like “what were the best video games released in 2017,” answers may be sourced from comments left in Reddit’s “gaming” subreddit or topic-specific forum.

People will also be able to use Bing to specifically search for content from Reddit. Typing “reddit [subreddit name]” will return a link to that subreddit and a selection of top comments that have been posted to it. And typing “reddit AMAs” will return a collection of popular AMA (“Ask Me Anything”) sessions, which are live question-and-answer forums that people can host on Reddit. Additionally, if people search for the name of a person who has a hosted an AMA on Reddit, a selection of responses from the Q&A session will appear among the non-Reddit results.

In addition to bringing Reddit’s data to Bing users, Microsoft is also opening that data up to brands. Brands will be able to access Reddit data through Microsoft’s Power BI analytics tool, with options to specify the keywords to track and toggle the time frames to examine. As a result, marketers will be able to monitor what people are saying about their brand or competing brands on Reddit and have that information processed using Power BI’s sentiment analysis feature and plotted into data visualizations.

The deal with Microsoft’s Power BI is similar to one that Reddit announced with social marketing platform Sprinklr last week in terms of accessing Reddit data. Brands will be able to see which subreddits they are mentioned on and then buy ads targeted those audiences.

Source: This article was published searchengineland.com By Tim Peterson

Categorized in Search Engine

These and many other insights are from Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series study. The study defines IoT as the network of physical objects, or "things," embedded with electronics, software, sensors, and connectivity to enable objects to collect and exchange data. The study examines key related technologies such as location intelligence, end-user data preparation, cloud computing, advanced and predictive analytics, and big data analytics. Please see page 11 of the study for details regarding the methodology. For an excellent overview of Internet of Things (IoT) predictions for 2018, please see Gil Press' post, 10 Predictions For The Internet Of Things (IoT) In 2018.

"Although still early days for IoT, we see this as a defining topic for the industry. IoT Intelligence, the means to understand and leverage IoT data, will likewise grow in importance and will elevate key technologies such as location intelligence, advanced and predictive analytics, and big data," said Howard Dresner, founder and chief research officer at Dresner Advisory Services.


Key takeaways from the study include the following:

  • Business Intelligence Competency Centers (BICC), R&D, Marketing & Sales and Strategic Planning are most likely to see the importance of IoT.Finance is considered among the least likely departments to see the importance of IoT. The study also found that sales analytics apps are increasingly relying on IoT technologies as foundational components of their core application platforms.
Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series Study
  • Manufacturing, Consulting, Business Services and Distribution/Logistics are IoT industry adoption leaders. Conversely, Federal Government, State & Local Government are least likely to prioritize IoT initiatives as very important or critical. IoT early adopters are most often defining goals with clear revenue and competitive advantages to drive initiatives. Manufacturing, Consulting, Business Services and Distribution/Logistics are challenging, competitive industries where revenue growth is often tough to achieve. IoT initiatives that deliver revenue and competitive strength quickly are the most likely to get funding and support.
Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series Study
  • IoT advocates or early adopters say location intelligence, streaming data analysis, and cognitive BI to deliver the greatest business benefit.Conversely, IoT early adopters aren’t expecting to see as significant of benefits from data warehousing as they are from other technologies. Consistent with previous studies, both the broader respondent base and IoT early adopters place a high priority on reporting and dashboards. IoT early adopters also see the greater importance of visualization and end-user self-service.

Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series Study
  • Business Intelligence Competency Centers (BICC), Manufacturing and Supply Chain are among the most powerful catalysts of BI and IoT adoption in the enterprise. The greater the level of BI adoption across the 12 functional drivers of BI adoption defined in the graphic below, the greater the potential for IoT to deliver differentiated value based on unique needs by area. Marketing, Sales and Strategic Planning are also strong driver areas among IoT advocates or early adopters.
Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series Study
  • IoT early adopters are relying on growing revenue and increasing competitive advantage as the two main goals to drive IoT initiatives’ success. The most successful IoT advocates or early adopters evangelize the many benefits of IoT initiatives from a revenue growth position first. IoT early adopters are more likely to see and promote the value of better decision-making, improved operational efficiencies, increased competitive advantage, growth in revenues, and enhanced customer service when BI adoption excels, setting the foundation for IoT initiatives to succeed.

Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series Study
  • The most popular feature requirements for advanced and predictive analytics applications include regression models, textbook statistical functions, and hierarchical clustering. More than 90% of respondents replied that these three leading features are “somewhat important” to their daily use of analytics. Geospatial analysis (highly associated with mapping, populations, demographics, and other Web-generated data), recommendation engines, Bayesian methods, and automatic feature selection is the next most required series of features.
Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series Study
  • 74% of IoT advocates or early adopters say location intelligence is critical or very important. Conversely, only 26% of the overall sample ranks location intelligence at the same level of importance. One of the most promising use cases for IoT-based location intelligence is its potential to streamline traceability and supply chain compliance workflows in highly regulated manufacturing industries. In 2018, expect to see ERP and Supply Chain Management (SCM) software vendors launch new applications that capitalize on IoT location intelligence to streamline traceability and supply chain compliance on a global scale.
Dresner Advisory Services’ 2017 Edition IoT Intelligence Wisdom of Crowds Series Study
Source: This article was published forbes.com By Louis Columbus
Categorized in Internet of Things

In today’s ultra-competitive business environment, you need all the tools you can get to have that edge over your rivals. And in this respect, BI takes on a very important role. Modern business and organizations strive on data. We’re talking of data that accumulates day in and day out, and that becomes what many call big data. On its own, data that keeps growing everyday has no tactical or strategic benefit to a business. But when that data is processed and analyzed to unravel trends, patterns and other useful insights, then data becomes an asset that provides real value to a business or organization. Extracted information can provide you useful insights on what is going on inside and outside your organization which you can use as basis for crucial decisions.

Current technology is now leveraged to give you the most accurate means to discover facts and events while they are happening and to predict challenges and issues before they happen. These are to keep your business fluid and ready for current and future business conditions. BI enables you to transform big raw data into comprehensible information that are oftentimes visualized in interactive dashboards which can further be queried and filtered to come up with more relevant insights.


What are the benefits of BI?

The current crop of business intelligence tools available in the market integrates the commonly used functionalities in BI such as analytics, reporting and visualization. Here are some of the benefits you can derive from BI:

  • It provides relevant insights. You can identify areas for improvement, determine market position, measure product viability, gauge supply and demand, spot sales opportunities, improve lead generation, learn customer behavior, and many more. You remove guess work and apply analytical information to optimize business processes, tasks and activities.
  • It gives a bird’s eye view. Decision makers get an overall picture of corporate performance through typical BI features like dashboards and scorecards. You can customize metrics, KPIs and milestones to align with your business strategies and objectives, and plot your business’ health across a threshold range.
  • It centralizes data. Instead of logging into several applications, systems and sources, you get collated and filtered information in real-time from a central hub, drastically reducing time to export and import data. Having data under one roof translates to efficiency and savings.
  • It streamlines business processes. BI takes out the complication associated with business processes since it automates analytics – a complex task that combines statistics, predictive analysis, computer modeling, benchmarking and other methodologies – so you don’t have to do the calculations yourself, and free you up to focus on other important matters and decisions.
  • It allows for easy analytics. Previously, analytics was an expensive, cumbersome, resource and labor intensive undertaking that required a whole IT team to handle for days at a time. Now, BI software has democratized its usage, allowing even non-analysts and ordinary users to promptly collect and process data, eventually putting the power of analytics from the hands of the few to the hands of the many.

Overview of the BI sector

Big data, analytics and business intelligence software are experiencing record growth. According to Forbes, three factors are driving big data, analytics and BI market: the shift by enterprises into a more customer-focused approach, the effort to improve operational performance, and the entry of businesses to new markets and adopting new business models. We take a look at some facts and figures about this software sector.

Market Situation

The latest forecast from Gartner shows continued growth in global revenue for the BI and analytics software market that is expected to reach $18.3 billion in 2017, or an increase of 7.3% from 2016. The market is forecast to reach $22.8 billion by the end of 2020.

BI Statistics

A KPMG survey of 400 U.S. CEOs reveals the following:

  • 51% use data analytics to develop new products and services
  • 50% use analytics to drive process and cost efficiency
  • 49% use data analytics to find new customers
  • 48% use analytics to drive strategy and change
  • 46% use analytics to manage risk
  • 44% use data and analytics to analyze existing customer needs, value, profitability, and likelihood of customer to defect

Importance of BI Trends 2017  Source bi-survey

BI Trends

The BI landscape continues to evolve because of technology and new business challenges. The following are some of the top business intelligence and analytics trends that you should be aware of.

  • Artificial Intelligence – Gartner’ technology trend report for 2017places AI on #1 spot. AI and machine learning now undertake complex tasks usually done by human intelligence. This capability is being leverage to come up with real-time data analysis and dashboard reporting to see situations as they are happening every second, with machines doing the tasks autonomously.
  • Collaborative BI – These are business intelligence softwarecombined with collaboration tools, including social media, and other latest technologies to enhance the working together and sharing by teams of data and information for collaborative decision-making. The term “self-service BI” falls into this category since it covers BI tools that anyone outside the IT team can use to access and interpret data.
  • Embedded BI – This involves the integration of BI software or some of its features into another business application to extend its analytics or reporting functionality. Capabilities usually specific to BI software are embedded into another non-BI application thereby streamlining data collection and analyses. This will spawn the “analytics everywhere” environment.
  • Cloud Analytics – Because of its more affordable cost and shorter deployment time, more BI applications will be offered in the cloud and more businesses will be shifting to this technology. In fact, according to IDC predictions through 2020 the spending on cloud-based big data and analytics will grow 4.5x faster than on-premise solutions.

Cloud BI vs On-Premise BI Strategy  Source - datapine

Top 5 business intelligence software solutions


Sisense is a multi-awarded business intelligence software and widely recognized as one of the best end-to-end BI platform that carry all the tools you need to prepare, analyze and visualize complex data. Users can consolidate all their data into visually appealing dashboards through a drag and drop user interface and generate valuable insights that can be shared with anyone. It is the preferred BI software for many companies, from startups to well-known brands such as Sony, ESPN, eBay, Rolls Royce, Motorola, Airbus and NASA, among others.

It boasts of instant deployment with its Single-Stack architecture that eliminates the need for additional tools to handle the process from data integration to visualization. It’s innovative In-chip engine allows you to ask any question and get immediate answers without returning to the drawing board for each new query. It is ideal for non-IT users needing to crunch and analyze big data and produce insights as well as visualized reports in a matter of minutes.

There are several benefits Sisense can offer. Among these are:

  • Consolidating all information from all sources into a single, accessible repository.
  • Generating rich and smart analysis using robust visual reports sans the hassle of preparation.
  • Analyzing data accurately and in real-time.
  • Handling the full range of BI tasks and processes.
  • Shortest time-to insight with its fast engine and end-to-end functionality.
  • Easy sharing of insights with your team, clients and partners.
  • Intuitive interface allowing non-tech users to quickly adapt with the system.
  • Speedy system that optimizes the potentials of 64-bit computer and multi-core CPUs.
  • Easy integration with other products and apps with its REST API.
  • Minimal cost of ownership since it is already a complete package.


Looker is a popular business intelligence software that specializes in data discovery. It applies an innovative approach to data exploration by leveraging a little SQL knowledge to examine data and collaborate company-wide to build efficient data models about your business. Being proficient in SQL and Web-based data, Looker can work with over 25 different variations and can support Google BigQuery, Spark, Vertica, Hive and several others. You can build analytics modules and models, run your queries, analyze entire data sets, and go through millions of items in your database. Looker is designed for heavy-duty stuff.

One of the many highlights of Looker is its collaboration feature where data projects or data sets can be saved as Git projects, allowing developers to track changes to their SQL code and enabling individuals to work together on a project. Visualization is straightforward, permitting multi-sized objects on the dashboard, adding new mapping features, or even importing visuals into Looker. It also supports Webhooks, permitting you to apply Looker data objects into third-party workflows. Since it is a Web app that runs on your browser, it is multi-device capable and can be operated on laptops, desktops, smartphones and tablets.

Looker provides you the following advantages:

  • 100% in-database and 100% browser-based platform.
  • Self-service features for filtering, pivoting, and creating of visualizations and dashboards.
  • No complicated coding, most operations come down to a single, self-intuitive code.
  • Personalized workspaces allow assigning of roles such as Administrators, Users, and Developers.
  • Mapping feature available for inexperienced users preparing highly technical visualizations.
  • Enables and streamlines collaboration among users.
  • Easy integration with different apps or custom and third-party applications.
  • Comes with easy-to-learn language called LookML that simplifies development of powerful models and enhances SQL capabilities.
  • Reliable tech support team can be reached via phone, email, or by sending ticket directly from Looker platform.


GoodData is a comprehensive cloud analytics platform that combines enterprise-level security, scalability, performance and powerful analytics to provide customer and operational insights, accelerate sales, and identify revenue opportunities. It integrates data with operational sources to help companies make smarter decisions, budget resources more efficiently, and boost predictability. GoodData is designed as a flexible analytic solution that aims to elevate business processes and drive revenue without compromising the functionality and performance of your existing systems and applications, or increasing IT and development spending.

What differentiates GoodData from other BI systems is its marketing analytics function that allows businesses and marketers to understand the behavior and needs of their customers. This extra functionality transforms your business data into revenue generating assets, facilitating sales performance and corporate profitability. With insights from marketing and customer data, you are able to launch data products in shorter time, helping you monetize your data assets. In addition, GoodData is able to handle data warehousing, self-service data discovery, advanced analytics and visualization, Big Data-ready ETL/ELT, and many others, all in one user-friendly cloud analytics platform. It manages your company’s technology and data pipeline with its unique collective learning capabilities that enable users to become better analysts.

Some key advantages of GoodData include:

  • Customer insights to measure marketing’s impact on your business.
  • Operational insights that optimizes decision-making.
  • Embedded analytics which opens opportunities for new revenue streams.
  • Data Explorer allows IT teams to be proactive and productive enhancing turnaround of insights with new sources of data in minutes.
  • Analytical Designer enables business users to do their own data discovery.
  • Leverages collective learning across the cloud environment to enhance productivity.
  • Email sharing and collaboration make it easy to tailor and share insights across the organization.
  • Data analysts maintain ownership of source systems and visibility of data lineage through the entire pipeline.
  • Flexible workspace management enables decentralized analyst productivity while maintaining centralized production level environment control.


Domo is a robust cloud-based, self-service BI tool built to operate your entire business, handle all your data, and run on any device at unprecedented speeds. This reliable GoodData alternative offers the widest data set and connector support, and provides unique social collaboration features. With Domo, you are able to connect your people with the data they need to make smarter and faster decisions; discover hidden opportunities in your business data; work better together to quickly act and capitalize on opportunities; and take actions on insights anytime and anywhere. The app’s social sharing function enables online discussions, commenting and sharing of results. You can also send individual messages or receive update notifications for every data element.

Domo gives you the ability to view data from a single dashboard in real-time. Its interface, dashboard widgets and displays are top-notch and visually appealing, incorporating creative data displays like sparklines, trend indicators and multi-part widgets. Domo allows you to combine various data sets with standard SQLs or to build personalized model cases from cloud and local data to come up with comprehensible data visualizations and actionable insights. You can connect quickly, easily and directly to over 450 data sources anywhere in your organization such as on-premise databases, cloud applications, spreadsheets, files, and more.

Here are some of the many benefits you can derive from Domo:

  • Easy data access with a flexible array of data connection options.
  • Effective visualizations with the freedom to visualize your data any way you want.
  • Fully mobile-optimized for anytime, anywhere operation.
  • Uniquely social platform gathers insights from people’s conversations, context, interests, and behaviors.
  • Open ecosystem allows anyone to build and deliver apps to Domo’s Appstore.
  • Domo University provides database full of support reports, testimonial videos, whitepapers and interactive lessons.
  • Built to operate at scale, complete with enterprise-grade data and security controls.


Tableau is a popular self-service analytics solution that comes in three variants: as an online platform, a desktop app for analysts, and a server version for enterprises. Whatever platform you choose, you get a sophisticated system with cutting-edge tools to help you understand and visualize company data. It is designed to fulfill any data analytics need and is equipped with plenty of connectors and visualizations. You can opt to work with live data or load them altogether to Tableau; once data sources are connected the app goes to work on preparing and cleaning the data based on your parameters.

There is a variety of visualization options to help you build dashboards and reports in minutes. Thanks to fast a processing engine and powerful analytics you can quickly connect to sources, visualize data, and share as well as publish dashboards right from your Tableau platform, all without the need for programming background.

Here’s a rundown of the benefits Tableau offers:

  • Fast and easy connection to several data sources, and speedy data analysis.
  • Intuitive and easy interface makes possible data analysis with a few simple drag-and-drop moves.
  • Advanced collaboration facilitates group analytics, with most functionality collated on a public dashboard.
  • Many methods for data investigation that can be combined to produce richer insights.
  • Flexible pricing and deployment with three platform versions.

 Source: This article was published bigdata-madesimple.com By Alex Hillsberg

Categorized in Business Research

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