At present, nearly all the Qlik
big data users are not the data scientists, rather they are business users
who do not want to mine through everything. Business users just want a simple guiding
approach which helps them get information which is relevant and related to
them.
But as these business users want
to look at different segments of a big data repository, they might not always recognize
which segments they really want to look at.
So how can the advanced Qlik big
data solution handle this? You know how Qlik big data empowers the technical
and non-technical user to completely find out information, get new insights and
understand the whole story into their data.
Let us quickly start with recognizing
how advanced Qlik
big data solution approach to big data and what exactly it has to proffer
its users.
Understanding the Qlik
Big Data Approach:
Qlik is acknowledged to be a
pioneer for big data analytics and its management. Today, it has a user base of
48,000 customers, which is spread extensively across 100 countries. Qlik big
data platform offers efficient business intelligence solutions for the technical
and non-technical users, who use it to discover big data and figure out the
story behind it.
Qlik big data solutions offer
data exploration, data visualization and also discovering insights and enable
users to take sound decisions on the basis of their analysis to nurture their
businesses.
Billions of terabytes of data gets
generated through all types of businesses across the world that is called as “Big
Data”. Businesses perceive Big Data as a prospective source of information about
the needs and behavior of their target customers, partners, suppliers, markets
and products.
Thereby, making big data a
strategic and cost-effective asset for businesses across the globe! As a result,
businesses are always looking for efficient cloud business intelligence
solutions and technologies that allow everyone in the company to work with
data and provide them user-friendly tools to change and visualize the data to give
it relevance and context.
And for the similar reason, businesses
have turned to Qlik big data
solutions.
Check Out the Primary Methods
To Use Qlik Big Data:
While managing the big data, one
of the common worries is that not all the employees in a company are skillful
data scientists or even close to having any knowledge about it.
Therefore, there should be such
big data analytics platforms and techniques that enables and empowers each user
to perform correct operations on data and produce informative reports by using
it. Users require a handy and user-friendly guided analytics atmosphere to assist
the users manage and understand the “Big Data”.
Another challenge that users face
while working with big data is that they are expected to know which element or
segment of the whole big data repository they have to work with, but it is not that
simple for the non-technical users.
For overcoming these issues, Qlik
big data solutions comes up with a few methods that can be used independently
or in combination to work with the “Big Data”.
- In-memory Engine: Qlik’s Indexing Engine (QIX) can compress the big data to 10% of its original size that is enough for a few customers. Qlik big data solutions work through accommodating the compressed data within the in-memory and then load it from there.
- Chaining: Chaining is basically, linking different sections or subject-specific views to each other. It creates a logical connection between the application segments. Big data analysis and management gets simple through first segmenting bigger applications into the subject-specific views and after that linking it with each other by chaining.
- Segmentation: Big data becomes very easy to handle and visualize through dividing a big application into small segments on the basis of the categories, this process is called segmentation.
- Direct Discovery: Another method to manage big data is by direct discovery wherein, some data in small tables still exists in the in-memory, but a big chunk of data in large tables can be found in the database. The users get direct access to the external database if they need the data from the large tables. This is a hybrid approach that brings together the in-memory system and the external database storage system.
Take a Look at the Key
Benefits of Qlik Big Data:
·
- Qlik big data solutions offer an associative and improved user experience to the user through incorporating data through different data sources and connecting it sensibly. The associative engine resourcefully collects data from the different data sources and then indexes it to have a better understanding about the data structure.
- Qlik supports a massive assortment of user base and provides many services like guided analytics, collaboration and reporting, , data integration, self-service visualization and exploration, geographic and advanced analytics, AI capabilities and a lot more.
- Qlik big data solutions assist in making sense of big data through empowering the users with abilities to obtain data from different sources and utilize it to derive meaning out of it.
- Big data is a big reservoir of vital information and insights in business. Qlik big data technologies assists the business users to easily access that data, model and arrange it and then showcase it visually and explore it even better.
- Qlik big data tools empower each user in the company, irrespective of their skill set and help them explore and analyze big data resourcefully.
- Qlik big data tools can connect to different kinds of data sources such as Excel, XML. Or, big data sources like Cloudera, Hadoop, etc., and app-specific sources like SAP etc.
- Qlik’s associative engine enables connections between the data tables that make navigating into large data sets extremely easy. The users do not have to scroll-down in difficult rows and columns of the large data tables. This makes big data even more manageable.
Qlik big data solutions are a strong
technology offering its thousands of customers a stress-free data analytics,
management and data visualization experience and excellent scalability and
flexibility to acclimatize to the speedily changing big data landscape.
Hope these insights on Qlik
big data was useful to you and solved all your queries.
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