2020 January

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.

QlikView

  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.

Summary

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.

Happy 2020! DataLabs team celebrated New Year's Eve

2020 is already here, and DataLabs team had a great time welcoming it!

Although the weather wasn’t festive at all, we couldn’t help but feel the holiday spirit. After all, we had put some work in adorning our office and decorating the Christmas tree, so everyone was thoroughly excited when the long-awaited day finally came.

It was a late Friday afternoon when we left the office building and headed to a restaurant. It was a lovely place with a tasteful exterior and a relaxed, cozy ambiance.

First, we were served delicious canapés and an exquisite cheese plate. Next, the salads arrived. There was a beef salad, a seafood salad, and a peculiar grapefruit salad with feta and avocado. We also ordered potato wedges and a tasty grilled meat platter.

After the main course, we decided to take some photos since the restaurant offered a few nice backgrounds.

We even briefly revived our inner child by taking pictures in a vacant children’s room!

While eating dessert, we agreed on going to the central ice rink next. No matter how far from Christmassy the weather can be, the Dnipro’s central ice rink will fill anyone with the festive spirit. Brightly lit with yellow Christmas lights, it’s situated right across the magnificent Christmas tree.

There were lots of people that evening, and the area was buzzing with excitement, laughter, and joy. It was so contagious that even those of us who didn’t know how to skate decided to join in. With some teamwork, we all had fun and learned something new!

The finishing touch to the amazing evening was a nice stroll through the central park, which is exceptionally beautiful around this time of year.

2019 was wonderful, and we can’t wait to see what heights our company will reach in 2020.

Season’s greetings and Happy New Year to everyone!

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