Sisense vs. OLAP Enterprise BI Tools

Enterprise BI tools at a glance

Traditional enterprise BI tools are common in large organizations that handle vast amounts of data. Typically, they rely on Online Analytical Processing (OLAP) to join different data sources into a single source of truth called a Data Warehouse. While these solutions are designed for scalability, they require a significant investment of time, effort, and money as well as a staff with the technical expertise to operate them.

Sisense delivers functionality and scalability but replaces OLAP and data warehouses with its own, in-house developed technology: ElastiCube. The ElastiCube is a columnar database that can handle terabytes of data coming from disparate sources, but requires minimal technical knowledge, works on commodity hardware, and reacts flexibly to rapidly changing business requirements.

The Sisense difference

Open, Single-Stack™ architecture:
Sisense end-to-end, agile BI platform is built to eliminate the barriers between users and their business analytics software so they can make smarter, faster, data-driven decisions.

The end-to-end BI software includes everything you need for insights and customizations: database, ETL, analytics, visualizations, and an open API framework.

Data analytics capabilities

Full-stack BI software is meant to perform several different functions, core competencies being:

  • Data preparation: Joining data from multiple sources and creating a centralized repository (single source of truth) while maintaining the integrity of the data
  • Analysis: Querying the data to receive answers to predefined and ad-hoc questions in order to understand and improve business processes and outcomes
  • Visualizations and dashboard reporting: Displaying data and query results in pivot tables, charts, and other graphical representations

With OLAP-based enterprise BI you get inflexible analysis

OLAP technology relies on pre-aggregating results to pre-defined queries. Queries are complex and lengthy to set up and require professional knowledge (usually from IT). Typically they are calculated when the system is not being utilized by end-users, resulting in fast answers to pre-defined queries, but very limited support for ad-hoc queries. New questions coming from the business side, or ones that involve taking new data into account, could take weeks or more to answer, depending on the company’s IT and hardware resources.

Performing analysis in an OLAP system requires dedicated analysts and IT support. It does not democratize analytics and BI. It is not an effective self-service platform for a large organization. The potential of an OLAP system will be bottlenecked by an organization’s IT resources and skilled analyst pool.

With Sisense you get agile business intelligence

The ElastiCube can easily be augmented to include new data sources, with new data imports generated in hours rather than days and with minimal IT assistance. New data is added, and ETL functions performed, incrementally—thus resolving the need to restart every data import from scratch, reducing time-to-production, and enabling an agile environment that responds to change.
Users are empowered to mashup different data sources, experiment with data, and discover insights on their own, instead of relying on IT and dedicated analysts.

The In-Chip® Analytics engine enables Sisense to provide instant answers to ad-hoc queries. Furthermore, because it’s a visual environment using excel like functions for ETL, with no coding or scripting required—new queries can be made directly by non-technical (‘business’) users rather than having to go through IT.

Feature Comparison

Data preparation

Sisense: Strong and fast; minimal IT support required to add new data sources, prepare or clean data.
Traditional enterprise BI: Strong, but slow; creating new data imports are lengthy and requires extensive IT support.

Analysis

Sisense: In-Chip analytics engine provides near-immediate answers to both predefined and ad-hoc queries.
Traditional enterprise BI: Fast answers to pre-defined queries; very limited support for ad-hoc queries.

Reporting and visualizations

Sisense: Comes out of the box with advanced dashboard reporting and a rich library of visualizations.
Traditional enterprise BI: Requires add-ons and third party software.

Embedding insights

Sisense: Place data and analytics widgets anywhere (standalone apps, workflow tools, etc.) to bring data to users outside of just dashboards.
Traditional enterprise BI: Centered on reporting, dashboards, and visualizations.

Total cost of ownership

Understanding the full costs involved with a BI project requires more than just checking the “sticker price.”
Beyond the initial software costs, other factors that affect pricing include:

  • Hardware: upgrades might be required at the time of implementation or when scaling to larger datasets in the future
  • Implementation costs: resources that will need to be invested before the platform can actually be put to use
  • Operational costs: typically manifested in man-hours devoted by the IT department or external consultants to maintain and operate the BI platform

With OLAP-based enterprise BI you get expensive implementation and maintenance

Enterprise BI solutions that rely on OLAP cubes are expensive to implement and operate. These tools require large amounts of proprietary technical knowledge and human intervention.
Additionally OLAP cubes rely on aggregations of data and constantly duplicating the existing database, which requires spending more and more on storage as data volume grows, as well as technical skills needed to constantly perform the aggregations and modeling.

With Sisense you get minimal overhead

Traditional enterprise software might appear only slightly more costly than Sisense when examining only the initial price of the software. However, Sisense works on commodity hardware that has a typical implementation cycle of a few weeks rather than months and requires little to no IT support for day-to-day operations as it can be fully deployed without coding or scripting.

Comparison by cost factor

Software

Sisense: Low
Traditional enterprise BI: Moderate

Hardware

Sisense: Low; designed for commodity hardware.
Traditional enterprise BI: Vary according to data size; can become very high with larger datasets.

Implementation

Sisense: Low; requires minimal technical knowledge and IT support.
Traditional enterprise BI: High; requires specialized knowledge and can take months.

Operational

Sisense: Low; once the database is set up.
Traditional enterprise BI: High; maintenance and ongoing operations require continuous IT work

Total cost of ownership

Sisense: Low
Traditional enterprise BI: High

Long-term scalability

As businesses grow, so does the amount of data that needs to be processed by their BI software. There are three factors the software needs to scale to:

  • Bigger datasets: the organization has more historical data, and technological developments allow it to collect more real-time data
  • More data sources: new business venues and software tools create entirely new datasets, which were not in place when the BI software was initially implemented
  • More users: more people work in the company, and more people need access to the BI platform

With OLAP-based enterprise BI you have difficulty scaling

OLAP enterprise BI tools handle huge databases; these databases become very difficult to maintain and control when data gets big, requiring more storage space and computational
resources. Additionally, and as mentioned above, adding new data sources is a complex task that must be left to IT.

With Sisense you get easy augmentation and scalability

The ElastiCube makes it easy to add new data sources as it requires little to no coding. New builds are generated incrementally and quickly—in minutes rather than days. The platform
scales to terabytes without losing performance, and Crowd Speed means the system actually performs faster when the number of concurrent users grows.

Comparison by scalability factor

Dataset size

Sisense: Terabyte-scale.
Enterprise BI: Terabyte-scale, but becomes difficult to maintain.

New data sources

Sisense: Add easily and quickly.
Enterprise BI: Lengthy and complicated.

More concurrent users

Sisense: Works faster with more users and more unique queries being made.
Enterprise BI: Entails significant hardware upgrades, particularly if new queries are being made.

Complexity and ease of use

The complexity of a BI solution affects every aspect of its use in the organization—from operational costs to company-wide adoption to plain usability. Complexity and ease of use can be measured in three aspects:

  • Implementation: getting the BI solution up and running
  • Maintenance: adding new data sources, ensuring the integrity of the contained data
  • Operations: getting answers to queries quickly, even as data and users increase

With OLAP-based enterprise BI you get technical and IT-centric tools

Setting up and maintaining an OLAP cube requires advanced technical and coding skills and is handled by the IT department. This applies both to creating the initial data warehouse, updating it to include additional data sources, and running queries when new business questions arise. Additionally, since OLAP systems demand well-defined requirements, it’s a slow process to define, consolidate, and then structure the data. This makes it time-consuming to initially create a cube but also to take into account changing requirements.

With Sisense you get a user-friendly, simple interface

Sisense simplifies every step of the BI journey and democratizes data handling and analysis for your entire organization. The majority of data preparation takes place in the ElastiCube using an intuitive drag and drop interface and without any coding or scripting. Automated features allow the Sisense platform to handle the bulk of integrating different sources with minimal human effort. More advanced datasets might require some IT support, but considerably less than with enterprise BI.

Once a build is generated, and a dashboard created, users with no technical expertise can run any query they can think of with no IT assistance. That’s true self-service.

Comparison by complexity factor

Implementation

Sisense: Mostly automated, possibly requiring minimal IT support; initial data import is rapidly developed, and new sources quickly added.
Traditional enterprise BI: Handled entirely by IT, typically takes months.

Maintenance

Sisense: Minimal IT intervention.
Traditional enterprise BI: IT is the project owner and is responsible for maintenance.

Operations

Sisense: Simple; handled entirely by non-technical end-users.
Traditional enterprise BI: Every operation runs through IT.

Summary

Sisense vs. Traditional OLAP Based Enterprise BI Software

CriteriaSisenseTraditional OLAP Based Enterprise BI
Standalone solutionYesNo
Scalability (1 server)TerabytesTerabytes
Time to productionDays/WeeksMonths/Years
Advanced end-user analyticsYesYes
Agility and scalabilityHighLow
Dashboard reportingYesRequires add-ons
Software costsLowMedium
Hardware costsLowHigh
Professional services costsLowHigh
Required technical expertiseLowHigh
Dependency on ITLowHigh
Embedded Analytics CapabilitiesYesNo

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