business intelligence

10 Big Data trends that accelerates business development

Technological advance and achievements instigated huge amount of data appearing. Many of us even don’t suppose that we’re producers of them. Every search request generates data and as a result we produce data in a few days more than in a decade in history. Received data has not to be just stored, it has power and effect if it is manipulated. Data is corporate assets that are used by different organizations to improve operative business. The reduction to practice of artificial intelligence (AI), machine learning (ML), IoT and other technologies improved the quality of data-driven business decisions. And it is not a hyperbolic affirmation «data makes business smarter».

Let’s get a view of 10 big data trends that accelerates business development:

1. Accessible AI

Big data that company has can generates value if it is processed using advanced technologies. For effective analyzing companies use: AI, ML and neural networks to forecast. However, to minimize technical readblocks there is cloud sources trend that essentially simplify data access. The hybrid cloud is capable to provide with more flexibility and possibilities to deploy data by moving processes between private and public clouds.

2. Continuous intelligence

Gartner explains continuous intelligence as a design pattern in which real-time analytics is integrated into business activity, processing current and historical data to prescribe actions in response to business events. Continuous intelligence use technologies like event stream processing, business rule management, ML, optimization and advanced analytics.

3. Advanced Analytics

Advanced Analytics is a part of data science. It uses ML and AI to improve analytics across all data life cycle (from the preparatiom method to analyzing). This technology promotes development of business flexibility, rapidly and credible information gaining, data sharing, and cutting time for information extracting and understanding. More detailed information in the entry «More analytics – more possibilities».

4. DataOps and self-service analytics

DataOps is a newish term, but it already is in favor in IT world. DataOps is a technology mix of continuous integration designed to afford actual data for every process member rapidly and fluently. With the help of this companies have a possibility to rise speed and improve data management quality.

Self-service analytics is a kind of analytics whereby users have an opportunity to make data requests and generate reports by themselves. Self-service analytics implementation allows to receive quick and exact result, simplify information sourcing all across chain.

5. Data-backed tools

Currently data for business processes is generated from all sides. The essential accelerator of this became IoT devices influence. Therefore, it instigated problems appearing. The fact of the matter is that data passes a long way to the centralized source.  But technologies allowed to avoid crisis. The edge computing conception allows to hold data in the local storage device near the IoT device for better data management.

6. Smart chat-bots

Chat-bots became an indispensable contact source between the business and consumers. With the help of this tool companies process customers’ requests and establish more personalized cooperation with them herewith reduce a real staff necessity. Chat-bots are based on big data as a connection source needs large data sets to work in the personalized format. Big data is the main source of the information transfer to chat-bots.

7. Intelligent security

One of the biggest business problems is a security threat. Using big data in a corporate security strategy it is possible to get essential profit. As big data contains all information concerning previous cyberattack attempts, phishing attacks, ransomware etc. it is possible to forecast, prevent and cushion an impact of future attempts.

8. Big data as a service (BDaaS)

BDaaS is a suite of big data analyzing methods and cloud computing platforms with the help of which it is possible to manage big data in cloud and provide their access at any time and for every user. Also, BDaaS promotes cost and time saving to deploy big data projects.

9. Dark data

Dark data is a part of big data that stays in the background. It is collected in consequence of specific network operations that aren’t covered by analytics. However, such data can have more value as one can imagine. Also, dark data can create a business security threat. That’s why it’s necessary to recover it or use correctly.

10. Cloud usage

Companies show a high interest in cloud technologies. This may be due to the fact that they able to change management methods of information and technologies business resources, providing their efficiency, security, flexibility, safety, automation, accessibility and optimization.

Main data trends 2021

After 2020 everyone has feelings that the world will not be the same. It was enough restless and astable year for the whole word. But at the same time, it became an acceleration of digital transformation processes. Business and people had to accustom and fit into a new reality. Less digitized companies have become more vulnerable during the pandemic compared to high-tech market players. However, it also became a motivation for such companies to run digital. They had to digitize their processes, upgrade business-models, provide access to data and advanced training for team. COVID-19 has also become a proof that the data plays a big role, and everyone can use it to inform or misinform.

Data science evolves and matures and consequently many organizations try to increase their digital stability and switch over to the data-driven model. Critical important tasks like self-driven car development, protein folding, and algorithmic trading programs have been conducted using data science methodologies and technologies. It’s just a little part of examples. Data science using is much wider, new and improved data science tools will appear in the coming years.

The main data trends and forecasts for 2021

1. Forecasts with the help of data analytics

One of the main 2021 trends will become real-time analytics. According to forecasts, the number of connected to Internet of Things devices will reach 24,1B by 2030. Organizations collect much more data than previously and try to transform it into analytic information that can help to solve business tasks. Real-time analytics transforming data into insights gives a possibility to respond to situation instantaneously.

2. Databases

For the last 40 years companies have histed their databases locally. However, in 2021 and the coming years there will be a trend of databases deploying or migration to the cloud. According to forecasts, cloud databases will grow up to 75% by 2022. It is a reason of different requirements appearing that most likely will come with developing on cloud-native databases, more closely incorporating analytical and machine learning capabilities.

3. Knowledge graph

As the amount of data still grows rapidly, it becomes increasingly difficult to analyze it. Knowledge graph can help in this by closing the gap between human and machine. In the minds of Gartner, it is one of the main data trends.

Knowledge graph has a form of a facts set (description of objects, conceptions and events) connected by typed links. It becomes possible to create a better context for data through linking and semantic metadata. It promotes easy analysis, integration, sharing and data aggregation.

4. Augmented analytics

We generate about 2500 petabytes of data every day and in 5 years this number will grow to 463 exabytes. Data increasing created serious problems in its processing. Augmented analytics can help to solve them. Using ML and AI methods big data transforms into massively smaller and analyzable one. According to the Gartner research augmented analytics will become a driver of BI in 2021.

5. Data Visualization

Data visualization became a perfect assistant in 2020 that helped to understand current situation easier. Creating, critical understanding and evaluation of data visualization will become a fundamental skill for everyone.

Qlik: Gartner's Magic Quadrant Leader

Recently Gartner has published the annual report where gives information about conditions of analytic platforms and business analytics, market and its trends. According to the report, Qlik has a dominant position of Gartner’s Magic Quadrant for analytics and BI platforms for 11th consecutive year.

«Qlik – is a leader in this Magic Quadrant. It has a strong product vision for ML and AI-driven augmentation».

Qlik’s strengths and benefits that were signed in the report:

Full report you can download HERE

Gartner Quadrant Leaders for Analytics and BI: Qlik Sense vs Microsoft Power BI vs Tableau

At this moment in time, the responsibility for analytics has shifted from IT staff to business analysts, database administrators, and data scientists. Thus, BI has gone from generating monthly reports from the record system to interactively creating and sharing forecasts and responding to business questions based on data from an extensive range of internal and external data sources. Before, businesses made decisions in a month. Now, thanks to self-service BI, they can take action in just a few days.

The problem is with the abundance of BI platforms available on the market today, it’s not easy to choose one that will suit your business needs perfectly. In this blog post we won’t be talking about tons of different BI tools but focus only on the heavyweights of self-service BI – Qlik Sense, Microsoft’s Power BI, Tableau. We’ll analyze and compare some of their main parameters to help you decide which one will be the most useful for your organization.

Qlik Sense


Qlik is the leading visual analytics platform and the forerunner of user-driven business intelligence. Its portfolio of cloud-based and on-premise solutions meet the growing customers’ demands ranging from reporting and self-service visual analysis to guided, embedded, and custom analytics, regardless of where data is stored. Qlik users gain meaningful insights exploring the hidden relationships within data from multiple sources. A fully integrated cloud platform, Qlik is powered by its unique in-memory associative data indexing (QIX) engine. Qlik’s Associative engine identifies and assembles all your data so you can explore without limits. This is easily the most powerful competitive advantage in a data-driven world.

Intuitive visualization and exploration, advanced analytics, and self-service data preparation abilities allow Qlik Sense to combine enterprise governance and readiness enabling organizations to manage the range of BI use cases from a single platform.

Let’s explore some of the key features of Qlik Sense:

Smart visualizations and analytics


Qlik Sense is not just a visualization tool. It offers advanced and intelligent visualizations that enhance the process of data analysis. The visualizations are interactive, flexible, and adjustable, with the first-rate graphics. There are many great visualizations types available like Distribution chart, Box plot, and Histogram that help users better understand their data. Users can also improve consistency in their application by applying custom coloring filters to data values within the master dimensions.

Conversational analytics and NLP

Thanks to the open API’s, Qlik has integration with the natural language generation & processing, advanced predictive analytics, and augmented intelligence. These capabilities make possible direct data exchange between third-party and QIX engine for calculations. Based on this interface, Qlik has released integrations for R and Python as well. As a result, users can visualize advanced calculations from external tools within Qlik Sense. But what’s more, Qlik users can combine the power of Qlik’s associative model with advanced analytics to support use cases like- sales forecasting, inventory management, and fraud detection.

Data storytelling and reporting

Data storytelling is one of the most powerful and unique features of Qlik Sense. It gives intelligent and in-context commentary on the data analytics visuals. The software creates the entire data story that puts things into perspective and paints a picture that will be presented for the analysis. It’s very helpful for drawing actionable insights from the data. The apps created in Qlik Sense in the form of reports can be printed or exported in Excel, PowerPoint, PDF, or other formats.


Qlik Sense was created with the mobility feature in mind. With its native touch interaction and responsive design, it allows you to explore analytics and collaborate with your team using any device. Moreover, you can experience fully interactive offline analysis on iOS, and it also supports leading Enterprise Mobility Management (EMM) platforms.

Scalability and governance

Qlik provides enterprise-class management services that guarantee data safety, control, monitoring, and centralized management. The centralized data monitoring and management are done via the Qlik Management Console (QMC) which controls all the Qlik Sense services centrally. Scalability is another crucial aspect. Elastic scaling in Qlik Sense helps to load and analyze a large amount of data.

Qlik Data Catalyst (QDC) and Attunity

Today’s hyper-competitive environment, where real-time enterprise data is indispensable to success, calls for a more agile approach to analytics and data integration. Qlik fuses Attunity’s data integration solutions with the data management and cataloging solutions of Qlik Data Catalyst and offers users an enterprise data integration platform to convert their raw data into a governed, analytics-driven information resource. This platform encourages the movement of data in real-time across multiple cloud environments and data lakes. When combined with predictive analytics and AI, it scales real-time insights throughout an entire organization.

Qlik Insight Bot (QIB)

Qlik Insight Bot offers a fast and simple way to ask questions and discover insights to make data-driven decisions just by having a conversation. With each question, the Qlik Insight Bot engages users and instantly brings up relevant charts and insights, including key drivers, comparisons, predictions, and more. Its self-learning AI makes the system progressively smarter.

Microsoft Power BI


Microsoft released its data visualization tool to the general public in 2015 under the name Power BI. 4 years later Gartner recognized Microsoft as a leader in “2019 Gartner Magic Quadrant for Analytics and Business Intelligence Platform” due to Power BI’s capabilities. Presently, Microsoft offers Power BI as a part of the Office 365 suit which contributes to its popularity even more.

It’s easy to understand why equally small and big business analysts adore this tool. Business users who have comprehensive knowledge of Excel intuitively understand Power BI. The same goes for technical users who are likely to adopt Microsoft Office stack. In terms of building and display, Power BI is a nice tool that offers visual data discovery and data preparation along with interactive dashboards and augmented analytics.

You can choose between Power BI Reporting Server (PBRS) option or a SaaS option in the Azure cloud in Power BI Report Server. It’s user-friendly and doesn’t require much time to create and share reports. The cloud option doesn’t entail infrastructure support but if you plan to deploy it on-premise, naturally you’ll need support no matter the size of your organization.

Now let’s take a look at some of the prominent features of Power BI that have made it a leader in Gartner’s BI Quadrant.

Appealing visualizations and robust data modeling


One of the main features of Power BI is the ability to personalize information dashboards according to your business needs. You can easily embed BI reports and create an interactive in-depth analysis for powerful data storytelling that will inspire your business users to embark on their data discovery journey. There are in-built visuals and custom visualizations created by the community available. After deciding on perfect visualization, you can get down to drill-ups and drill-downs.

As for data modeling, Power BI has a query editor. It’s an integrated ETL tool that allows you to work with data from numerous data sources to build effective data models. It is powered by a Data engine that can deal with complex enterprise use cases. In addition, Python and R that are integrated with Power BI open the door for advanced analytics, visualization, and data mining.

Smooth integration with applications

Regardless of your Microsoft product being deployed in cloud or on-premise, the integration with Power BI is smooth. It integrates flawlessly with legacy as well as modern enterprise applications and perfectly visualizes available data. Power BI has different in-built connectors that easily connect and join multiple on-cloud, on-premise, and streaming data sources to use it for data preparation. Furthermore, it supports integration with Cortana, Excel, and many other applications and services.

Fresh insights with DAX

DAX (data analysis expressions) is a collection of functions and operators, that can be used for data analysis and calculations. Microsoft developed this functional language to interact with data in Power BI, PowerPivot, and SSAS Tabular. Although for some DAX concepts may seem simple, DAX itself is quite powerful. With it, data analysts can create new measures and obtain unique insights into data through exclusive visualizations.

Promising product roadmap ahead

Since Microsoft’s Power BI is a relatively new product on the BI market, it can be improved even more. Even now, new features and enhancements are available every month. Microsoft monitors users’ requests about the features and prioritizes those that are in high demand. Regarding licenses, Power BI has several – Power BI Desktop (free), Power BI Pro, and Power BI Premium. There are also many Power BI communities that help users find solutions and suggestions to a variety of problems.



Founded in 2003, Tableau is an enterprise-scale business analytics platform with self-service capabilities. Tableau’s dashboards present organizations with an interactive interface that comes with a depth of colors, visualization options, and a robust analytics engine. Users can combine large data sources and access them instantly without the need to rely on their IT team. You can securely access Tableau through native applications even on Android and iOS.

Tableau’s popularity is accounted for by easy deployment, support, and usability. It’s a tool focused primarily on data visualization so if that’s what you’re looking for, then Tableau may be your pick. Let’s take a moment to consider what it has to offer.

In-depth insights


With Tableau, organizations can analyze data even without any particular goal in mind. This method of exploring and visualizing data from different angles may lead to sudden useful realizations and insights. You can frame ‘what if’ queries and operate data hypothetically visualizing it in different and dynamic ways by adding components for comparison and analysis.

Engage different data sources

While analyzing, you can pull data from many sources like cloud, spreadsheets, data warehouses, etc. Tableau’s data blending feature will help you blend all the data in the visuals while keeping them apart at the source. This method simultaneously accelerates the process of combining data from multiple sources and negates the need for priming data before processing it for the visuals.

Real-time data analysis

Data is changing fast so it’s important to keep your dashboards always updated. Tableau gives you the ability to make live connections with the database. When there are new entries or changes in the database, you can refresh in Tableau and see all the changes reflect on your dashboard. It’s also possible to set specific time intervals for the data to refresh. This will help you draw valuable insights in real-time.

Drag-and-drop clustering

This may be the most powerful feature of Tableau since it allows you to combine similar group members. “How is it helpful?’, you may ask. With grouping, you get statistical information that will help you see similarities between different groups as well as compare their performance for segmentation analysis.

Tableau Online

Tableau Online is a fully hosted cloud solution that offers immediate setup and efficient scalability for enhancing business growth. It’s a platform where you can publish and share your discoveries with other people. You can invite customers or teammates to further explore hidden opportunities using interactive visualizations and accurate data.


By and large, all these tools work following different principles. Qlik Sense is more than a visualization tool. It has a strong and unique ETL engine and connectors that can connect you to any kind of source system. Power BI is a fantastic asset for quick insights, great user experience, and collaboration within your company. Lastly, if you want a simple interface and beautiful visualizations, Tableau might be your preferred choice. Usually, discussions may come more around commercials or individual preferences, but if it is an end-to-end BI and you don’t have anything for your ETL or Data Warehouse, then Qlik may be a better fit.

Qlik makes cloud analytics more accessible to every customer

Qlik announced new packaging and adoption programs that will give customers more options and make cloud-based analytics simpler and more cost-effective to adapt. These programs comprise new packaging of Qlik Sense Enterprise with SaaS only as well as Client-Managed options. Additionally, QlikView customers can easily adopt Qlik Sense Enterprise SaaS and host their QlikView documents in the cloud at the same time.

James Fisher, the Chief Product Officer of Qlik stated, “Customers are eager to leverage the scale and cost efficiencies of analytics in the cloud, and at the same time leverage augmented and actionable analytics to turn insights into action.” He added that with their latest Qlik Sense offering and new Analytics Modernization Program “it’s easier than ever for every Qlik customer to adopt and leverage cloud-based analytics and benefit from new AI and cognitive technologies across their entire organization.”

In the second quarter of 2020, Qlik customers will be able to coordinate the deployment of Qlik analytics with their IT strategies more effectively via two options, SaaS or Client-Managed. Those who choose Qlik Sense Enterprise SaaS will reduce management issues and minimize infrastructure costs by deploying exclusively in Qlik’s cloud. Meanwhile, customers who go for Qlik Sense Enterprise Client-Managed can deploy either on-premise or in a private cloud depending on their governance or data requirements. They can also license both and make the most of Qlik’s unique multi-cloud architecture.

Qlik’s Analytics Modernization Program will further provide QlikView customers with expanded flexibility and choice. It allows them to adopt Qlik Sense steadily, at their own pace without disruption to existing QlikView operations.

Steph Robinson, Qlik Manager Business Intelligence IT at JBS USA said, “We’re excited about the growing adoption of analytics we’re seeing in our employee base with Qlik Sense”. He noted they continue to leverage QlikView apps that have been already created but also give their developers an opportunity to adopt Qlik Sense at their own pace. “Being able to leverage our existing QlikView apps, while also extending analytics capabilities through Qlik Sense, has accelerated our journey to modern BI and is helping our organization become more data-driven”.

The Analytics Modernization Program opens up the following possibilities for QlikView users:

Doug Henschen, VP and Principal Analyst at Constellation Research pointed out, “As organizations increasingly migrate applications and data to the cloud, they look to maximize the value of that data to drive strategic advantage.” He continued saying that “by providing these new options to move analytical workloads to the cloud as quickly and easily as possible, Qlik is responding to growing customer expectations and where we see the industry headed.”

Other exciting developments Qlik Sense customers should look forward to are various new features in the April Qlik Sense release that will help them broaden analytics adoption through the cloud. Among new elements, there will be new visualization and dashboarding enhancements, the ability to share charts, notifications within the management console, and improved data file management and data connections for data flow into individual Qlik Sense workflows.

Qlik becomes a part of Snowflake Partner Connect Program

This week Qlik partnered with Snowflake, a cloud data warehouse. The partnership involves Qlik’s integration with the Snowflake Partner Connect program which will provide Snowflake customers with a two-week free trial to fully experience Qlik’s first-class data integration software. The free trial comprises tutorials for swiftly ingesting and delivering data in real-time to Snowflake. Extension of the trial enables users to export data from numerous popular enterprise database systems, mainframes and SAP applications. With Qlik Data Integration platform, it’s also possible to automate the creation and updates of analytics-ready data sets in Snowflake.

“Our customers want to accelerate their modernization efforts by utilizing highly performant and robust solutions to replicate data into Snowflake,” stated Colleen Kapase, Snowflake VP of WW Partners and Alliances. “With Qlik’s real-time data integration capabilities, customers will realize an immediate benefit to easily bringing that data directly into Snowflake. We are excited about Qlik joining our partner connect program, bringing new capabilities for customers to modernize to Snowflake.”

Snowflake Partner Connect empowers new users to effortlessly connect with and integrate specific Snowflake business partners straight into their experience when creating trial accounts. With Qlik Data Integration, customers can access a wide selection of enterprise data sources in real-time and gain the most value during a Snowflake evaluation. After completion of the trial, there is an easy way to purchase the full license of Qlik Data Integration.

“Snowflake gives us a scalable data lake environment, bringing data together in one location from any source. This enhances decision making across all our varied business functions, including manufacturing, supply chain, customer service, and financing,” affirmed Dallas Thornton, Director of Digital Services at PACCAR. “Qlik’s data integration software is a huge driver in the value we see with Snowflake. Since it streams disparate data sources using change data capture into Snowflake from any platform – be it cloud, x86 databases, mainframes, or AS400 – our users now have one environment in Snowflake from which to analyze data in near real-time.”

“We’re excited to expand our partnership with Snowflake by joining their partner connect program, helping enterprises accelerate their journey to cloud data warehousing,” proclaimed Itamar Ankorion, SVP Technology Alliances at Qlik. “Qlik has a complete solution for Snowflake that continuously ingests all targeted data, automates the warehouse/mart creation without scripting, and makes data and insights readily accessible across the organization with world-class analytics.”

About Qlik

Qlik’s vision is a data-literate world, one where everyone can use data to improve decision-making and solve their most challenging problems. Only Qlik offers end-to-end, real-time data integration and analytics solutions that help organizations access and transform all their data into value. Qlik helps companies lead with data to see more deeply into customer behavior, reinvent business processes, discover new revenue streams, and balance risk and reward. Qlik does business in more than 100 countries and serves over 50,000 customers around the world.

Qlik became a Gartner Magic Quadrant leader for the 10th year in a row!

Yesterday Qlik announced they had been named a Gartner’s Magic Quadrant Leader for Analytics and BI Platforms for 10th year in a row. This recognition marks not only a decade of Qlik’s continuous leadership in the quadrant but also inclusion in Gartner’s MQ since 2006.

“Qlik is helping customers accelerate business value through data, providing a full range of capabilities to go from raw data to real-time insights and action,” said Mike Capone, CEO of Qlik. “Our company continues to grow profitably, and our strong performance has enabled us to invest in delivering an end-to-end platform that includes data integration, AI-driven insights, and conversational analytics. With our recent acquisition of RoxAI we are providing automated intelligent alerting for real-time decision making as we continue to invest in capabilities that increase data’s value for every organization.”

The report, which Gartner releases annually in February, provides an unbiased evaluation of analytics and business intelligence (ABI) platforms, analyses the market and highlights its biggest trends. This time, an appraisal of the platforms is no longer based on their data visualization capabilities since those are becoming mainstream. Instead, the focus is shifting towards integrated support for enterprise reporting capabilities and augmented analytics.

“Machine learning (ML) and artificial intelligence (AI)-assisted data preparation, insight generation, and insight explanation — to augment how business people and analysts explore and analyze data — are fast becoming key sources of competitive differentiation, and therefore core investments, for vendors.” – Gartner, 2020

Gartner lists the following strengths of Qlik:

“Empowering employees with the right information and the confidence to make decisions with it is vital,” said Director of Business Intelligence, Visualization and Reporting at Nationwide Building Society. “Qlik has proven to be fantastic in helping to consolidate disparate data, break down internal silos and drive value. By making data more visible and intuitive, business teams have gained new insights across many processes, increasing efficiency and fostering a data-enabled culture.”

You can download a copy of the full report here.

Qlik's Statement of Direction 2020: Exciting developments from Qlik that are waiting for us in 2020 and beyond

As we’re stepping into a new decade, Qlik releases their Statement of Direction which provides an exciting overview of Qlik’s product direction and forthcoming offers. We encapsulated this fascinating read into 15 sentences that should hype you up for using the Qlik Analytics Platform in 2020 and beyond.

Qlik Sense

  1. New capabilities for customers to add business logic to the Qlik Cognitive Engine, and new sources for machine learning – including governed libraries, the analytics ecosystem and external, domain specific sources.
  2. New types of augmented analysis which include key driver analysis, statistical, predictive and prescriptive insights as well a new extension for multi-attribute (cohort) analysis.
  3. Improvements for advanced analytics integration performance, augmented data stories and content recommendations.
  4. New visualization, analytics and authoring capabilities that include moving averages, difference functions, time-based forecasting, trend indicators in tables and sparklines.
  5. Introduction of grid and bullet charts.
  6. Dynamic views, a new capability enabling in-memory database views for products such as Snowflake, SAP HANA and more.
  7. Check out / check in functionality for app objects supporting team-based development.
  8. New self-service reporting that will support authoring, scheduling and personalized distribution.
  9. A new user experience for insight management that will allow people to capture, organize, share and take action on the most relevant insights – including charts, AI-generated insights, snapshots, reports, stories and more.
  10. Annotations and discussion threads, content following and social BI in a multi-cloud hub, an insight library with tasks, goals and approvals, and workflow automation through the platform.

Qlik Sense Mobile

  1. Automatic downloads of updated offline apps and support for offline mashups.

Qlik Insight Bot

  1. Integration with the Qlik Cognitive Engine, allowing for enhanced natural language capabilities surfaced in visual and conversational user experiences.

Qlik NPrinting

  1. Integration of report distribution capabilities directly into Qlik Sense.


  1. Common scheduling with Qlik Sense

Qlik Connectors

  1. Configurable REST connectivity with Azure Data Lake, updates to Essbase connectivity, integrated connectivity to new data sources such as Amazon Athena, and expanded support for SAP HANA.

If you’d like to read Qlik’s Statement of Direction 2020, you can find it here.


The Statement of Direction 2020 suggests that from now on Qlik will be focusing on integration. They’ve acquired many great additions such as RoxAI and their Ping solution to build up a multidimensional platform, but unfortunately it lacks integration. That’s why it’s so amazing to see Qlik working on this issue while also advancing the field of analytics and expanding their platform with new additions that soon will combine into a powerful unit.

Data and Analytics trends that will transform business landscape in 2020 and beyond

Modern businesses must deal with colossal amount of data which can be overwhelming. On the flip side, being able to obtain insights from the massive pool of data is beneficial since it helps to make well-informed decisions that propel growth. Brand new BI, data and analytics technologies emerge all the time and it’s important to recognize and embrace those that will help your business gain a competitive edge.

But don’t wait until new technologies grow and mature! Don’t be afraid to engage with them and explore their capabilities. Through trial and error, you’ll be able to find a solution that suits the needs of your company best. At the same time, BI and analytics service providers ought to adopt new technologies to provide their clients with competitive advantage.

We present you the list of data and analytics trends that will shape the business landscape in 2020 and beyond.

Augmented Analytics

Coined by Gartner in 2017, the term Augmented analytics refers to the use of AI, machine learning and natural language processing to enhance data preparation, data analytics and business intelligence.

To glean insights from data, one needs to collect and analyze it. These tasks are the responsibility of data scientists who spend approximately 80% of their time only on data preparation. The remaining 20% is spent on putting this data to good use. With augmented analytics, the initial stages of this procedure can be automated. What’s more, the goal is to get rid of data scientist altogether and even entrust search for insights to AI. Although this should speed up the process of making business decisions, it requires adequate data literacy among employees.

According to Gartner report, augmented analytics are expected to influence the increase in purchasing ML, data science and BI solutions.

Augmented Data Management

Data is collected from various resources so It’s not surprising data scientists spend a lot of time refining it. Augmented Data Management (ADM) allows businesses to cleanse data automatically using artificial intelligence and machine learning. Thus, organizations can eliminate unnecessary and tedious work of data scientists, speed up their productivity and ensure the quality of the data. What’s more, ADM can be useful for data engineers. It will notify them about potential errors and data issues and offer alternative interpretations of data.

ADM will likely cause a big splash during the following years. Gartner predicts that by the end of 2022 ADM will reduce manual tasks by 45%. Further reliance on AI and ML will reduce the need for data management specialists by 20% by 2023.

NLP and Conversational Analytics

Natural Language Processing (NLP) is a branch of AI that makes conversation between humans and machines possible. It’s a technology that allows computers understand written and spoken human language. The most prominent examples where NLP is used are Google, Grammarly, Interactive Voice Response, Siri, Cortana, Amazon Alexa, etc.

NLP grants businesses an ability to inquire into data and gain better understanding of generated reports. Conversational analytics is a technology based on NLP that can provide insight into how users interact with your chatbots or other AI-based interfaces in real time.

Data analytics tools can be demanding, but with NLP, even non-specialists will be able to request information from databases and other less structured sources of information with no effort.  According to Gartner, by 2021, companies will adopt BI and analytics tools for more than half of their employees comparing to 35% of employees that use such tools now. Among new types of users there will be a company’s front-office staff.

Graph analytics

An emerging and exciting form of data analysis, graph analytics works exceptionally well with visualizing complex relationship between data. It utilizes graph format to represent data points as nodes and relationship as edges. This format is the most suitable for finding indirect connections between data points or analyzing data based on the quality and strength of the relationship.

Graph analytics prove to be useful in various fields such as logistics, traffic route optimization, social network analysis, fraud detection, and more. As businesses continue to explore capabilities of big data, graph analytics will become a must-have for deriving a more complex and profound insights. Gartner predicts that in the forthcoming years application of graph analytics will grow at a rate of 100% annually.

Commercial Machine Learning and Artificial Intelligence

Nowadays AI and ML market is dominated by open-source platforms like Python, Apache Spark and R, but, according to Gartner, it’s about to change. Open-source platforms were supposed to democratize the market and make advanced technology available to everyone. Sure, most innovations pertaining to algorithms and development environment over the last five years have occurred on open-source platforms. But open source has some serious drawbacks when it comes to scalability of AI and ML.

At Gartner, they estimate that by 2022 75% of new ML and AI solutions will be based on commercial rather than open-source platforms. Commercial vendors, which at first were slow to adapt, are finally catching up by establishing connectors to open-source ecosystem. Furthermore, they’re introducing features necessary for scaling AI and ML on the enterprise level, e.g. project and model management, transparency, data lineage, platform integration etc. Thus, businesses can combine innovations of open-source platforms with enterprise-ready tools offered by commercial vendors and deploy models in production more efficiently.

Logi Analytics received the highest vendor rating for embedded BI according to Dresner

In the recent Embedded BI Market Study by Dresner Advisory Services, Logi Analytics has received the highest rating out of 15 vendors. The study has recognized Logi as number one for the fifth consecutive year.

“While Embedded BI is still eclipsed by marquee BI practices such as reporting and dashboards, it ranks ahead of other widely discussed initiatives such big data, Internet of Things, and social media analysis,” said Jim Ericson, VP and research director at Dresner Advisory Services. “We continue to observe that embedded BI remains on a long-term uptrend and retains high importance in organizations.”

The Dresner study result isn’t the only accolade Logi Analytics has earned this year. In October, Logi was rated as the top embedded BI vendor in The BI Survey 19 from the Business Application Research Center (BARC). Earlier this year, for the fourth time in a row, Logi got a top score for OEM and embedded BI in the Gartner’s 2019 Critical Capabilities for Analytics and Business Intelligence Platforms.

“Most applications are becoming analytic applications, with dashboards, reports, data visualizations, and predictive analytics at their core,” said Steven Schneider, CEO of Logi Analytics. “Logi is proud to help some of the smartest software leaders in the world embed analytics in their applications. Being named the leader for the fifth year in a row by Dresner validates the important work our customers are doing.”

This is the seventh annual Dresner Advisory Services report on Embedded Business Intelligence, and it’s a part of the “Wisdom of Crowds” market survey series.

About Logi Analytics

Logi Analytics is the leading analytics platform focused on embedding analytics in commercial and enterprise applications. Founded in 2000 as LogiXML, the company helped web developers easily embed data into websites. Nowadays, Logi is a powerful platform that gained trust of over 2100 application teams who use it to create more valuable applications, engage users, and differentiate their software products.

The company’s headquarters are in McLean, Virginia, U.S. with offices in the UK and Ireland.

About Dresner Advisory Services

Dresner Advisory Services is an independent advisory firm founded by Howard Dresner, a notable thought leader in the BI sphere and performance management who coined the term “Business Intelligence” in 1989. Over the past 20 years, he has conducted numerous in-depth researches and is an expert in analyzing BI market.

Through the unbiased, non-sponsored, and crowd-sourced Wisdom of Crowds® market research, Dresner Advisory Services provides an alternative perspective on Business Intelligence and related markets.

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